Datasets:

NyanDoggo

/

bird-vanilla-alpaca

like 0

Solve the following sql problem: What are the issues of the complains of male clients and products from age 25 and below? Schema: SCHEMA: - Table: state - Column: StateCode - Samples: [AL, AR, AZ, CA, CO] - Column: State - Samples: [Alabama, Arkansas, Arizona, California, Colorado] - Column: Region - Samples: [South, South, West, West, West] - Table: callcenterlogs - Column: Date received - Samples: [2017-03-27, 2017-03-27, 2017-03-27, 2017-03-23, 2017-03-22] - Column: Complaint ID - Samples: [CR2406263, CR2405641, CR2405629, CR2400594, CR2399607] - Column: rand client - Samples: [C00004587, C00003328, C00001685, C00001945, C00004303] - Column: phonefinal - Samples: [977-806-9726, 322-598-7152, 508-311-5237, 265-394-2727, 206-008-0460] - Column: vru+line - Samples: [AA0103, AA0205, AA0110, AA0113, AA0102] - Column: call_id - Samples: [34536, 34537, 34538, 34540, 34541] - Column: priority - Samples: [0, 0, 2, 2, 1] - Column: type - Samples: [NW, PS, PS, PS, PS] - Column: outcome - Samples: [AGENT, AGENT, AGENT, AGENT, AGENT] - Column: server - Samples: [MICHAL, TOVA, YIFAT, AVNI, STEREN] - Column: ser_start - Samples: [13:34:11, 10:58:22, 13:00:54, 16:18:21, 14:48:22] - Column: ser_exit - Samples: [13:40:23, 11:16:10, 13:13:31, 16:19:40, 14:55:19] - Column: ser_time - Samples: [00:06:12, 00:17:48, 00:12:37, 00:01:19, 00:06:57] - Table: client - Column: client_id - Samples: [C00000001, C00000002, C00000003, C00000004, C00000005] - Column: sex - Samples: [Female, Male, Female, Male, Female] - Column: day - Samples: [13, 4, 9, 1, 3] - Column: month - Samples: [12, 2, 10, 12, 7] - Column: year - Samples: [1990, 1965, 1960, 1976, 1980] - Column: age - Samples: [29, 54, 59, 43, 39] - Column: social - Samples: [926-93-2157, 806-94-5725, 614-70-9100, 580-20-3414, 536-14-5809] - Column: first - Samples: [Emma, Noah, Olivia, Liam, Sophia] - Column: middle - Samples: [Avaya, Everest, Brooklynne, Irvin, Danae] - Column: last - Samples: [Smith, Thompson, Johnson, White, Williams] - Column: phone - Samples: [367-171-6840, 212-423-7734, 212-425-6932, 951-567-8925, 428-265-1568] - Column: email - Samples: [[email protected], [email protected], [email protected], [email protected], [email protected]] - Column: address_1 - Samples: [387 Wellington Ave., 75 W. Berkshire St., 36 Second St., 7607 Sunnyslope Street, 755 Galvin Street] - Column: address_2 - Samples: [Unit 1, None, None, None, None] - Column: city - Samples: [Albuquerque, New York City, New York City, Indianapolis, Indianapolis] - Column: state - Samples: [NM, NY, NY, IN, IN] - Column: zipcode - Samples: [47246, 10040, 10162, 49047, 40852] - Column: district_id - Samples: [18, 1, 1, 5, 5] - Table: district - Column: district_id - Samples: [1, 2, 3, 4, 5] - Column: city - Samples: [New York City, Jacksonville, Columbus, Charlotte, Indianapolis] - Column: state_abbrev - Samples: [NY, FL, OH, NC, IN] - Column: division - Samples: [Middle Atlantic, South Atlantic, East North Central, South Atlantic, East North Central] - Table: events - Column: Date received - Samples: [2014-07-03, 2012-04-12, 2012-04-03, 2012-03-14, 2012-03-05] - Column: Product - Samples: [Bank account or service, Bank account or service, Bank account or service, Credit card, Bank account or service] - Column: Sub-product - Samples: [Checking account, Savings account, Checking account, None, Checking account] - Column: Issue - Samples: [Deposits and withdrawals, Account opening, closing, or management, Account opening, closing, or management, Billing disputes, Account opening, closing, or management] - Column: Sub-issue - Samples: [None, None, None, None, None] - Column: Consumer complaint narrative - Samples: [None, None, None, None, None] - Column: Tags - Samples: [None, None, None, None, None] - Column: Consumer consent provided? - Samples: [N/A, N/A, N/A, N/A, N/A] - Column: Submitted via - Samples: [Email, Email, Email, Email, Email] - Column: Date sent to company - Samples: [2014-07-09, 2012-04-13, 2012-04-03, 2012-03-14, 2012-03-06] - Column: Company response to consumer - Samples: [Closed with explanation, Closed with relief, Closed without relief, Closed with relief, Closed with relief] - Column: Timely response? - Samples: [Yes, Yes, Yes, Yes, Yes] - Column: Consumer disputed? - Samples: [No, No, No, No, No] - Column: Complaint ID - Samples: [CR0922485, CR0057298, CR0043811, CR0035411, CR0030939] - Column: Client_ID - Samples: [C00001925, C00003141, C00000297, C00004275, C00000900] - Table: reviews - Column: Date - Samples: [2017-10-04, 2017-10-02, 2017-08-21, 2017-12-17, 2016-05-27] - Column: Stars - Samples: [5, 5, 5, 5, 5] - Column: Reviews - Samples: [Great job, Eagle National! Each person was professional and helped us ..., Matthew Richardson is professional and helpful. He helped us find the ..., We had a past experience with Eagle National Mortgage and would withou..., We have been dealing with Brad Thomka from the beginning of what start..., I can't express how grateful I am for the support that Zach provided t... (truncated)] - Column: Product - Samples: [Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage] - Column: district_id - Samples: [65, 66, 23, 55, 24]

SELECT DISTINCT T2.Issue FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.sex = 'Male' AND T1.age < 25

Solve the following sql problem: Among the reviews from midwest region, what are the products that received 1 star? Schema: SCHEMA: - Table: state - Column: StateCode - Samples: [AL, AR, AZ, CA, CO] - Column: State - Samples: [Alabama, Arkansas, Arizona, California, Colorado] - Column: Region - Samples: [South, South, West, West, West] - Table: callcenterlogs - Column: Date received - Samples: [2017-03-27, 2017-03-27, 2017-03-27, 2017-03-23, 2017-03-22] - Column: Complaint ID - Samples: [CR2406263, CR2405641, CR2405629, CR2400594, CR2399607] - Column: rand client - Samples: [C00004587, C00003328, C00001685, C00001945, C00004303] - Column: phonefinal - Samples: [977-806-9726, 322-598-7152, 508-311-5237, 265-394-2727, 206-008-0460] - Column: vru+line - Samples: [AA0103, AA0205, AA0110, AA0113, AA0102] - Column: call_id - Samples: [34536, 34537, 34538, 34540, 34541] - Column: priority - Samples: [0, 0, 2, 2, 1] - Column: type - Samples: [NW, PS, PS, PS, PS] - Column: outcome - Samples: [AGENT, AGENT, AGENT, AGENT, AGENT] - Column: server - Samples: [MICHAL, TOVA, YIFAT, AVNI, STEREN] - Column: ser_start - Samples: [13:34:11, 10:58:22, 13:00:54, 16:18:21, 14:48:22] - Column: ser_exit - Samples: [13:40:23, 11:16:10, 13:13:31, 16:19:40, 14:55:19] - Column: ser_time - Samples: [00:06:12, 00:17:48, 00:12:37, 00:01:19, 00:06:57] - Table: client - Column: client_id - Samples: [C00000001, C00000002, C00000003, C00000004, C00000005] - Column: sex - Samples: [Female, Male, Female, Male, Female] - Column: day - Samples: [13, 4, 9, 1, 3] - Column: month - Samples: [12, 2, 10, 12, 7] - Column: year - Samples: [1990, 1965, 1960, 1976, 1980] - Column: age - Samples: [29, 54, 59, 43, 39] - Column: social - Samples: [926-93-2157, 806-94-5725, 614-70-9100, 580-20-3414, 536-14-5809] - Column: first - Samples: [Emma, Noah, Olivia, Liam, Sophia] - Column: middle - Samples: [Avaya, Everest, Brooklynne, Irvin, Danae] - Column: last - Samples: [Smith, Thompson, Johnson, White, Williams] - Column: phone - Samples: [367-171-6840, 212-423-7734, 212-425-6932, 951-567-8925, 428-265-1568] - Column: email - Samples: [[email protected], [email protected], [email protected], [email protected], [email protected]] - Column: address_1 - Samples: [387 Wellington Ave., 75 W. Berkshire St., 36 Second St., 7607 Sunnyslope Street, 755 Galvin Street] - Column: address_2 - Samples: [Unit 1, None, None, None, None] - Column: city - Samples: [Albuquerque, New York City, New York City, Indianapolis, Indianapolis] - Column: state - Samples: [NM, NY, NY, IN, IN] - Column: zipcode - Samples: [47246, 10040, 10162, 49047, 40852] - Column: district_id - Samples: [18, 1, 1, 5, 5] - Table: district - Column: district_id - Samples: [1, 2, 3, 4, 5] - Column: city - Samples: [New York City, Jacksonville, Columbus, Charlotte, Indianapolis] - Column: state_abbrev - Samples: [NY, FL, OH, NC, IN] - Column: division - Samples: [Middle Atlantic, South Atlantic, East North Central, South Atlantic, East North Central] - Table: events - Column: Date received - Samples: [2014-07-03, 2012-04-12, 2012-04-03, 2012-03-14, 2012-03-05] - Column: Product - Samples: [Bank account or service, Bank account or service, Bank account or service, Credit card, Bank account or service] - Column: Sub-product - Samples: [Checking account, Savings account, Checking account, None, Checking account] - Column: Issue - Samples: [Deposits and withdrawals, Account opening, closing, or management, Account opening, closing, or management, Billing disputes, Account opening, closing, or management] - Column: Sub-issue - Samples: [None, None, None, None, None] - Column: Consumer complaint narrative - Samples: [None, None, None, None, None] - Column: Tags - Samples: [None, None, None, None, None] - Column: Consumer consent provided? - Samples: [N/A, N/A, N/A, N/A, N/A] - Column: Submitted via - Samples: [Email, Email, Email, Email, Email] - Column: Date sent to company - Samples: [2014-07-09, 2012-04-13, 2012-04-03, 2012-03-14, 2012-03-06] - Column: Company response to consumer - Samples: [Closed with explanation, Closed with relief, Closed without relief, Closed with relief, Closed with relief] - Column: Timely response? - Samples: [Yes, Yes, Yes, Yes, Yes] - Column: Consumer disputed? - Samples: [No, No, No, No, No] - Column: Complaint ID - Samples: [CR0922485, CR0057298, CR0043811, CR0035411, CR0030939] - Column: Client_ID - Samples: [C00001925, C00003141, C00000297, C00004275, C00000900] - Table: reviews - Column: Date - Samples: [2017-10-04, 2017-10-02, 2017-08-21, 2017-12-17, 2016-05-27] - Column: Stars - Samples: [5, 5, 5, 5, 5] - Column: Reviews - Samples: [Great job, Eagle National! Each person was professional and helped us ..., Matthew Richardson is professional and helpful. He helped us find the ..., We had a past experience with Eagle National Mortgage and would withou..., We have been dealing with Brad Thomka from the beginning of what start..., I can't express how grateful I am for the support that Zach provided t... (truncated)] - Column: Product - Samples: [Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage] - Column: district_id - Samples: [65, 66, 23, 55, 24]

SELECT DISTINCT T3.Product FROM state AS T1 INNER JOIN district AS T2 ON T1.StateCode = T2.state_abbrev INNER JOIN reviews AS T3 ON T2.district_id = T3.district_id WHERE T1.Region = 'Midwest' AND T3.Stars = 1

Solve the following sql problem: List the products involved in the complaints received on March 2017 via TOVA server. Schema: SCHEMA: - Table: state - Column: StateCode - Samples: [AL, AR, AZ, CA, CO] - Column: State - Samples: [Alabama, Arkansas, Arizona, California, Colorado] - Column: Region - Samples: [South, South, West, West, West] - Table: callcenterlogs - Column: Date received - Samples: [2017-03-27, 2017-03-27, 2017-03-27, 2017-03-23, 2017-03-22] - Column: Complaint ID - Samples: [CR2406263, CR2405641, CR2405629, CR2400594, CR2399607] - Column: rand client - Samples: [C00004587, C00003328, C00001685, C00001945, C00004303] - Column: phonefinal - Samples: [977-806-9726, 322-598-7152, 508-311-5237, 265-394-2727, 206-008-0460] - Column: vru+line - Samples: [AA0103, AA0205, AA0110, AA0113, AA0102] - Column: call_id - Samples: [34536, 34537, 34538, 34540, 34541] - Column: priority - Samples: [0, 0, 2, 2, 1] - Column: type - Samples: [NW, PS, PS, PS, PS] - Column: outcome - Samples: [AGENT, AGENT, AGENT, AGENT, AGENT] - Column: server - Samples: [MICHAL, TOVA, YIFAT, AVNI, STEREN] - Column: ser_start - Samples: [13:34:11, 10:58:22, 13:00:54, 16:18:21, 14:48:22] - Column: ser_exit - Samples: [13:40:23, 11:16:10, 13:13:31, 16:19:40, 14:55:19] - Column: ser_time - Samples: [00:06:12, 00:17:48, 00:12:37, 00:01:19, 00:06:57] - Table: client - Column: client_id - Samples: [C00000001, C00000002, C00000003, C00000004, C00000005] - Column: sex - Samples: [Female, Male, Female, Male, Female] - Column: day - Samples: [13, 4, 9, 1, 3] - Column: month - Samples: [12, 2, 10, 12, 7] - Column: year - Samples: [1990, 1965, 1960, 1976, 1980] - Column: age - Samples: [29, 54, 59, 43, 39] - Column: social - Samples: [926-93-2157, 806-94-5725, 614-70-9100, 580-20-3414, 536-14-5809] - Column: first - Samples: [Emma, Noah, Olivia, Liam, Sophia] - Column: middle - Samples: [Avaya, Everest, Brooklynne, Irvin, Danae] - Column: last - Samples: [Smith, Thompson, Johnson, White, Williams] - Column: phone - Samples: [367-171-6840, 212-423-7734, 212-425-6932, 951-567-8925, 428-265-1568] - Column: email - Samples: [[email protected], [email protected], [email protected], [email protected], [email protected]] - Column: address_1 - Samples: [387 Wellington Ave., 75 W. Berkshire St., 36 Second St., 7607 Sunnyslope Street, 755 Galvin Street] - Column: address_2 - Samples: [Unit 1, None, None, None, None] - Column: city - Samples: [Albuquerque, New York City, New York City, Indianapolis, Indianapolis] - Column: state - Samples: [NM, NY, NY, IN, IN] - Column: zipcode - Samples: [47246, 10040, 10162, 49047, 40852] - Column: district_id - Samples: [18, 1, 1, 5, 5] - Table: district - Column: district_id - Samples: [1, 2, 3, 4, 5] - Column: city - Samples: [New York City, Jacksonville, Columbus, Charlotte, Indianapolis] - Column: state_abbrev - Samples: [NY, FL, OH, NC, IN] - Column: division - Samples: [Middle Atlantic, South Atlantic, East North Central, South Atlantic, East North Central] - Table: events - Column: Date received - Samples: [2014-07-03, 2012-04-12, 2012-04-03, 2012-03-14, 2012-03-05] - Column: Product - Samples: [Bank account or service, Bank account or service, Bank account or service, Credit card, Bank account or service] - Column: Sub-product - Samples: [Checking account, Savings account, Checking account, None, Checking account] - Column: Issue - Samples: [Deposits and withdrawals, Account opening, closing, or management, Account opening, closing, or management, Billing disputes, Account opening, closing, or management] - Column: Sub-issue - Samples: [None, None, None, None, None] - Column: Consumer complaint narrative - Samples: [None, None, None, None, None] - Column: Tags - Samples: [None, None, None, None, None] - Column: Consumer consent provided? - Samples: [N/A, N/A, N/A, N/A, N/A] - Column: Submitted via - Samples: [Email, Email, Email, Email, Email] - Column: Date sent to company - Samples: [2014-07-09, 2012-04-13, 2012-04-03, 2012-03-14, 2012-03-06] - Column: Company response to consumer - Samples: [Closed with explanation, Closed with relief, Closed without relief, Closed with relief, Closed with relief] - Column: Timely response? - Samples: [Yes, Yes, Yes, Yes, Yes] - Column: Consumer disputed? - Samples: [No, No, No, No, No] - Column: Complaint ID - Samples: [CR0922485, CR0057298, CR0043811, CR0035411, CR0030939] - Column: Client_ID - Samples: [C00001925, C00003141, C00000297, C00004275, C00000900] - Table: reviews - Column: Date - Samples: [2017-10-04, 2017-10-02, 2017-08-21, 2017-12-17, 2016-05-27] - Column: Stars - Samples: [5, 5, 5, 5, 5] - Column: Reviews - Samples: [Great job, Eagle National! Each person was professional and helped us ..., Matthew Richardson is professional and helpful. He helped us find the ..., We had a past experience with Eagle National Mortgage and would withou..., We have been dealing with Brad Thomka from the beginning of what start..., I can't express how grateful I am for the support that Zach provided t... (truncated)] - Column: Product - Samples: [Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage] - Column: district_id - Samples: [65, 66, 23, 55, 24]

SELECT DISTINCT T2.Product FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T1.server = 'TOVA' AND T2.`Date received` LIKE '2017-03%'

Solve the following sql problem: What is the division of the review of 5 stars received on December 17, 2017 for the product Eagle National Mortgage? Schema: SCHEMA: - Table: state - Column: StateCode - Samples: [AL, AR, AZ, CA, CO] - Column: State - Samples: [Alabama, Arkansas, Arizona, California, Colorado] - Column: Region - Samples: [South, South, West, West, West] - Table: callcenterlogs - Column: Date received - Samples: [2017-03-27, 2017-03-27, 2017-03-27, 2017-03-23, 2017-03-22] - Column: Complaint ID - Samples: [CR2406263, CR2405641, CR2405629, CR2400594, CR2399607] - Column: rand client - Samples: [C00004587, C00003328, C00001685, C00001945, C00004303] - Column: phonefinal - Samples: [977-806-9726, 322-598-7152, 508-311-5237, 265-394-2727, 206-008-0460] - Column: vru+line - Samples: [AA0103, AA0205, AA0110, AA0113, AA0102] - Column: call_id - Samples: [34536, 34537, 34538, 34540, 34541] - Column: priority - Samples: [0, 0, 2, 2, 1] - Column: type - Samples: [NW, PS, PS, PS, PS] - Column: outcome - Samples: [AGENT, AGENT, AGENT, AGENT, AGENT] - Column: server - Samples: [MICHAL, TOVA, YIFAT, AVNI, STEREN] - Column: ser_start - Samples: [13:34:11, 10:58:22, 13:00:54, 16:18:21, 14:48:22] - Column: ser_exit - Samples: [13:40:23, 11:16:10, 13:13:31, 16:19:40, 14:55:19] - Column: ser_time - Samples: [00:06:12, 00:17:48, 00:12:37, 00:01:19, 00:06:57] - Table: client - Column: client_id - Samples: [C00000001, C00000002, C00000003, C00000004, C00000005] - Column: sex - Samples: [Female, Male, Female, Male, Female] - Column: day - Samples: [13, 4, 9, 1, 3] - Column: month - Samples: [12, 2, 10, 12, 7] - Column: year - Samples: [1990, 1965, 1960, 1976, 1980] - Column: age - Samples: [29, 54, 59, 43, 39] - Column: social - Samples: [926-93-2157, 806-94-5725, 614-70-9100, 580-20-3414, 536-14-5809] - Column: first - Samples: [Emma, Noah, Olivia, Liam, Sophia] - Column: middle - Samples: [Avaya, Everest, Brooklynne, Irvin, Danae] - Column: last - Samples: [Smith, Thompson, Johnson, White, Williams] - Column: phone - Samples: [367-171-6840, 212-423-7734, 212-425-6932, 951-567-8925, 428-265-1568] - Column: email - Samples: [[email protected], [email protected], [email protected], [email protected], [email protected]] - Column: address_1 - Samples: [387 Wellington Ave., 75 W. Berkshire St., 36 Second St., 7607 Sunnyslope Street, 755 Galvin Street] - Column: address_2 - Samples: [Unit 1, None, None, None, None] - Column: city - Samples: [Albuquerque, New York City, New York City, Indianapolis, Indianapolis] - Column: state - Samples: [NM, NY, NY, IN, IN] - Column: zipcode - Samples: [47246, 10040, 10162, 49047, 40852] - Column: district_id - Samples: [18, 1, 1, 5, 5] - Table: district - Column: district_id - Samples: [1, 2, 3, 4, 5] - Column: city - Samples: [New York City, Jacksonville, Columbus, Charlotte, Indianapolis] - Column: state_abbrev - Samples: [NY, FL, OH, NC, IN] - Column: division - Samples: [Middle Atlantic, South Atlantic, East North Central, South Atlantic, East North Central] - Table: events - Column: Date received - Samples: [2014-07-03, 2012-04-12, 2012-04-03, 2012-03-14, 2012-03-05] - Column: Product - Samples: [Bank account or service, Bank account or service, Bank account or service, Credit card, Bank account or service] - Column: Sub-product - Samples: [Checking account, Savings account, Checking account, None, Checking account] - Column: Issue - Samples: [Deposits and withdrawals, Account opening, closing, or management, Account opening, closing, or management, Billing disputes, Account opening, closing, or management] - Column: Sub-issue - Samples: [None, None, None, None, None] - Column: Consumer complaint narrative - Samples: [None, None, None, None, None] - Column: Tags - Samples: [None, None, None, None, None] - Column: Consumer consent provided? - Samples: [N/A, N/A, N/A, N/A, N/A] - Column: Submitted via - Samples: [Email, Email, Email, Email, Email] - Column: Date sent to company - Samples: [2014-07-09, 2012-04-13, 2012-04-03, 2012-03-14, 2012-03-06] - Column: Company response to consumer - Samples: [Closed with explanation, Closed with relief, Closed without relief, Closed with relief, Closed with relief] - Column: Timely response? - Samples: [Yes, Yes, Yes, Yes, Yes] - Column: Consumer disputed? - Samples: [No, No, No, No, No] - Column: Complaint ID - Samples: [CR0922485, CR0057298, CR0043811, CR0035411, CR0030939] - Column: Client_ID - Samples: [C00001925, C00003141, C00000297, C00004275, C00000900] - Table: reviews - Column: Date - Samples: [2017-10-04, 2017-10-02, 2017-08-21, 2017-12-17, 2016-05-27] - Column: Stars - Samples: [5, 5, 5, 5, 5] - Column: Reviews - Samples: [Great job, Eagle National! Each person was professional and helped us ..., Matthew Richardson is professional and helpful. He helped us find the ..., We had a past experience with Eagle National Mortgage and would withou..., We have been dealing with Brad Thomka from the beginning of what start..., I can't express how grateful I am for the support that Zach provided t... (truncated)] - Column: Product - Samples: [Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage] - Column: district_id - Samples: [65, 66, 23, 55, 24]

SELECT T1.division FROM district AS T1 INNER JOIN reviews AS T2 ON T1.district_id = T2.district_id WHERE T2.Stars = 5 AND T2.Date = '2017-12-17' AND T2.Product = 'Eagle National Mortgage'

Solve the following sql problem: In complaints about the credit card product, list the phone number of the oldest client. Schema: SCHEMA: - Table: state - Column: StateCode - Samples: [AL, AR, AZ, CA, CO] - Column: State - Samples: [Alabama, Arkansas, Arizona, California, Colorado] - Column: Region - Samples: [South, South, West, West, West] - Table: callcenterlogs - Column: Date received - Samples: [2017-03-27, 2017-03-27, 2017-03-27, 2017-03-23, 2017-03-22] - Column: Complaint ID - Samples: [CR2406263, CR2405641, CR2405629, CR2400594, CR2399607] - Column: rand client - Samples: [C00004587, C00003328, C00001685, C00001945, C00004303] - Column: phonefinal - Samples: [977-806-9726, 322-598-7152, 508-311-5237, 265-394-2727, 206-008-0460] - Column: vru+line - Samples: [AA0103, AA0205, AA0110, AA0113, AA0102] - Column: call_id - Samples: [34536, 34537, 34538, 34540, 34541] - Column: priority - Samples: [0, 0, 2, 2, 1] - Column: type - Samples: [NW, PS, PS, PS, PS] - Column: outcome - Samples: [AGENT, AGENT, AGENT, AGENT, AGENT] - Column: server - Samples: [MICHAL, TOVA, YIFAT, AVNI, STEREN] - Column: ser_start - Samples: [13:34:11, 10:58:22, 13:00:54, 16:18:21, 14:48:22] - Column: ser_exit - Samples: [13:40:23, 11:16:10, 13:13:31, 16:19:40, 14:55:19] - Column: ser_time - Samples: [00:06:12, 00:17:48, 00:12:37, 00:01:19, 00:06:57] - Table: client - Column: client_id - Samples: [C00000001, C00000002, C00000003, C00000004, C00000005] - Column: sex - Samples: [Female, Male, Female, Male, Female] - Column: day - Samples: [13, 4, 9, 1, 3] - Column: month - Samples: [12, 2, 10, 12, 7] - Column: year - Samples: [1990, 1965, 1960, 1976, 1980] - Column: age - Samples: [29, 54, 59, 43, 39] - Column: social - Samples: [926-93-2157, 806-94-5725, 614-70-9100, 580-20-3414, 536-14-5809] - Column: first - Samples: [Emma, Noah, Olivia, Liam, Sophia] - Column: middle - Samples: [Avaya, Everest, Brooklynne, Irvin, Danae] - Column: last - Samples: [Smith, Thompson, Johnson, White, Williams] - Column: phone - Samples: [367-171-6840, 212-423-7734, 212-425-6932, 951-567-8925, 428-265-1568] - Column: email - Samples: [[email protected], [email protected], [email protected], [email protected], [email protected]] - Column: address_1 - Samples: [387 Wellington Ave., 75 W. Berkshire St., 36 Second St., 7607 Sunnyslope Street, 755 Galvin Street] - Column: address_2 - Samples: [Unit 1, None, None, None, None] - Column: city - Samples: [Albuquerque, New York City, New York City, Indianapolis, Indianapolis] - Column: state - Samples: [NM, NY, NY, IN, IN] - Column: zipcode - Samples: [47246, 10040, 10162, 49047, 40852] - Column: district_id - Samples: [18, 1, 1, 5, 5] - Table: district - Column: district_id - Samples: [1, 2, 3, 4, 5] - Column: city - Samples: [New York City, Jacksonville, Columbus, Charlotte, Indianapolis] - Column: state_abbrev - Samples: [NY, FL, OH, NC, IN] - Column: division - Samples: [Middle Atlantic, South Atlantic, East North Central, South Atlantic, East North Central] - Table: events - Column: Date received - Samples: [2014-07-03, 2012-04-12, 2012-04-03, 2012-03-14, 2012-03-05] - Column: Product - Samples: [Bank account or service, Bank account or service, Bank account or service, Credit card, Bank account or service] - Column: Sub-product - Samples: [Checking account, Savings account, Checking account, None, Checking account] - Column: Issue - Samples: [Deposits and withdrawals, Account opening, closing, or management, Account opening, closing, or management, Billing disputes, Account opening, closing, or management] - Column: Sub-issue - Samples: [None, None, None, None, None] - Column: Consumer complaint narrative - Samples: [None, None, None, None, None] - Column: Tags - Samples: [None, None, None, None, None] - Column: Consumer consent provided? - Samples: [N/A, N/A, N/A, N/A, N/A] - Column: Submitted via - Samples: [Email, Email, Email, Email, Email] - Column: Date sent to company - Samples: [2014-07-09, 2012-04-13, 2012-04-03, 2012-03-14, 2012-03-06] - Column: Company response to consumer - Samples: [Closed with explanation, Closed with relief, Closed without relief, Closed with relief, Closed with relief] - Column: Timely response? - Samples: [Yes, Yes, Yes, Yes, Yes] - Column: Consumer disputed? - Samples: [No, No, No, No, No] - Column: Complaint ID - Samples: [CR0922485, CR0057298, CR0043811, CR0035411, CR0030939] - Column: Client_ID - Samples: [C00001925, C00003141, C00000297, C00004275, C00000900] - Table: reviews - Column: Date - Samples: [2017-10-04, 2017-10-02, 2017-08-21, 2017-12-17, 2016-05-27] - Column: Stars - Samples: [5, 5, 5, 5, 5] - Column: Reviews - Samples: [Great job, Eagle National! Each person was professional and helped us ..., Matthew Richardson is professional and helpful. He helped us find the ..., We had a past experience with Eagle National Mortgage and would withou..., We have been dealing with Brad Thomka from the beginning of what start..., I can't express how grateful I am for the support that Zach provided t... (truncated)] - Column: Product - Samples: [Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage] - Column: district_id - Samples: [65, 66, 23, 55, 24]

SELECT T1.phone FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.Product = 'Credit card' ORDER BY T1.age DESC LIMIT 1

Solve the following sql problem: In complaints received in 2014, how many of them were submitted via call? Schema: SCHEMA: - Table: state - Column: StateCode - Samples: [AL, AR, AZ, CA, CO] - Column: State - Samples: [Alabama, Arkansas, Arizona, California, Colorado] - Column: Region - Samples: [South, South, West, West, West] - Table: callcenterlogs - Column: Date received - Samples: [2017-03-27, 2017-03-27, 2017-03-27, 2017-03-23, 2017-03-22] - Column: Complaint ID - Samples: [CR2406263, CR2405641, CR2405629, CR2400594, CR2399607] - Column: rand client - Samples: [C00004587, C00003328, C00001685, C00001945, C00004303] - Column: phonefinal - Samples: [977-806-9726, 322-598-7152, 508-311-5237, 265-394-2727, 206-008-0460] - Column: vru+line - Samples: [AA0103, AA0205, AA0110, AA0113, AA0102] - Column: call_id - Samples: [34536, 34537, 34538, 34540, 34541] - Column: priority - Samples: [0, 0, 2, 2, 1] - Column: type - Samples: [NW, PS, PS, PS, PS] - Column: outcome - Samples: [AGENT, AGENT, AGENT, AGENT, AGENT] - Column: server - Samples: [MICHAL, TOVA, YIFAT, AVNI, STEREN] - Column: ser_start - Samples: [13:34:11, 10:58:22, 13:00:54, 16:18:21, 14:48:22] - Column: ser_exit - Samples: [13:40:23, 11:16:10, 13:13:31, 16:19:40, 14:55:19] - Column: ser_time - Samples: [00:06:12, 00:17:48, 00:12:37, 00:01:19, 00:06:57] - Table: client - Column: client_id - Samples: [C00000001, C00000002, C00000003, C00000004, C00000005] - Column: sex - Samples: [Female, Male, Female, Male, Female] - Column: day - Samples: [13, 4, 9, 1, 3] - Column: month - Samples: [12, 2, 10, 12, 7] - Column: year - Samples: [1990, 1965, 1960, 1976, 1980] - Column: age - Samples: [29, 54, 59, 43, 39] - Column: social - Samples: [926-93-2157, 806-94-5725, 614-70-9100, 580-20-3414, 536-14-5809] - Column: first - Samples: [Emma, Noah, Olivia, Liam, Sophia] - Column: middle - Samples: [Avaya, Everest, Brooklynne, Irvin, Danae] - Column: last - Samples: [Smith, Thompson, Johnson, White, Williams] - Column: phone - Samples: [367-171-6840, 212-423-7734, 212-425-6932, 951-567-8925, 428-265-1568] - Column: email - Samples: [[email protected], [email protected], [email protected], [email protected], [email protected]] - Column: address_1 - Samples: [387 Wellington Ave., 75 W. Berkshire St., 36 Second St., 7607 Sunnyslope Street, 755 Galvin Street] - Column: address_2 - Samples: [Unit 1, None, None, None, None] - Column: city - Samples: [Albuquerque, New York City, New York City, Indianapolis, Indianapolis] - Column: state - Samples: [NM, NY, NY, IN, IN] - Column: zipcode - Samples: [47246, 10040, 10162, 49047, 40852] - Column: district_id - Samples: [18, 1, 1, 5, 5] - Table: district - Column: district_id - Samples: [1, 2, 3, 4, 5] - Column: city - Samples: [New York City, Jacksonville, Columbus, Charlotte, Indianapolis] - Column: state_abbrev - Samples: [NY, FL, OH, NC, IN] - Column: division - Samples: [Middle Atlantic, South Atlantic, East North Central, South Atlantic, East North Central] - Table: events - Column: Date received - Samples: [2014-07-03, 2012-04-12, 2012-04-03, 2012-03-14, 2012-03-05] - Column: Product - Samples: [Bank account or service, Bank account or service, Bank account or service, Credit card, Bank account or service] - Column: Sub-product - Samples: [Checking account, Savings account, Checking account, None, Checking account] - Column: Issue - Samples: [Deposits and withdrawals, Account opening, closing, or management, Account opening, closing, or management, Billing disputes, Account opening, closing, or management] - Column: Sub-issue - Samples: [None, None, None, None, None] - Column: Consumer complaint narrative - Samples: [None, None, None, None, None] - Column: Tags - Samples: [None, None, None, None, None] - Column: Consumer consent provided? - Samples: [N/A, N/A, N/A, N/A, N/A] - Column: Submitted via - Samples: [Email, Email, Email, Email, Email] - Column: Date sent to company - Samples: [2014-07-09, 2012-04-13, 2012-04-03, 2012-03-14, 2012-03-06] - Column: Company response to consumer - Samples: [Closed with explanation, Closed with relief, Closed without relief, Closed with relief, Closed with relief] - Column: Timely response? - Samples: [Yes, Yes, Yes, Yes, Yes] - Column: Consumer disputed? - Samples: [No, No, No, No, No] - Column: Complaint ID - Samples: [CR0922485, CR0057298, CR0043811, CR0035411, CR0030939] - Column: Client_ID - Samples: [C00001925, C00003141, C00000297, C00004275, C00000900] - Table: reviews - Column: Date - Samples: [2017-10-04, 2017-10-02, 2017-08-21, 2017-12-17, 2016-05-27] - Column: Stars - Samples: [5, 5, 5, 5, 5] - Column: Reviews - Samples: [Great job, Eagle National! Each person was professional and helped us ..., Matthew Richardson is professional and helpful. He helped us find the ..., We had a past experience with Eagle National Mortgage and would withou..., We have been dealing with Brad Thomka from the beginning of what start..., I can't express how grateful I am for the support that Zach provided t... (truncated)] - Column: Product - Samples: [Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage] - Column: district_id - Samples: [65, 66, 23, 55, 24]

SELECT COUNT(T2.`Complaint ID`) FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T2.`Submitted via` = 'Phone' AND strftime('%Y', T1.`Date received`) = '2014'

Solve the following sql problem: List the product and its issues of the complains of clients with age greater than the 60% of average age of all clients. Schema: SCHEMA: - Table: state - Column: StateCode - Samples: [AL, AR, AZ, CA, CO] - Column: State - Samples: [Alabama, Arkansas, Arizona, California, Colorado] - Column: Region - Samples: [South, South, West, West, West] - Table: callcenterlogs - Column: Date received - Samples: [2017-03-27, 2017-03-27, 2017-03-27, 2017-03-23, 2017-03-22] - Column: Complaint ID - Samples: [CR2406263, CR2405641, CR2405629, CR2400594, CR2399607] - Column: rand client - Samples: [C00004587, C00003328, C00001685, C00001945, C00004303] - Column: phonefinal - Samples: [977-806-9726, 322-598-7152, 508-311-5237, 265-394-2727, 206-008-0460] - Column: vru+line - Samples: [AA0103, AA0205, AA0110, AA0113, AA0102] - Column: call_id - Samples: [34536, 34537, 34538, 34540, 34541] - Column: priority - Samples: [0, 0, 2, 2, 1] - Column: type - Samples: [NW, PS, PS, PS, PS] - Column: outcome - Samples: [AGENT, AGENT, AGENT, AGENT, AGENT] - Column: server - Samples: [MICHAL, TOVA, YIFAT, AVNI, STEREN] - Column: ser_start - Samples: [13:34:11, 10:58:22, 13:00:54, 16:18:21, 14:48:22] - Column: ser_exit - Samples: [13:40:23, 11:16:10, 13:13:31, 16:19:40, 14:55:19] - Column: ser_time - Samples: [00:06:12, 00:17:48, 00:12:37, 00:01:19, 00:06:57] - Table: client - Column: client_id - Samples: [C00000001, C00000002, C00000003, C00000004, C00000005] - Column: sex - Samples: [Female, Male, Female, Male, Female] - Column: day - Samples: [13, 4, 9, 1, 3] - Column: month - Samples: [12, 2, 10, 12, 7] - Column: year - Samples: [1990, 1965, 1960, 1976, 1980] - Column: age - Samples: [29, 54, 59, 43, 39] - Column: social - Samples: [926-93-2157, 806-94-5725, 614-70-9100, 580-20-3414, 536-14-5809] - Column: first - Samples: [Emma, Noah, Olivia, Liam, Sophia] - Column: middle - Samples: [Avaya, Everest, Brooklynne, Irvin, Danae] - Column: last - Samples: [Smith, Thompson, Johnson, White, Williams] - Column: phone - Samples: [367-171-6840, 212-423-7734, 212-425-6932, 951-567-8925, 428-265-1568] - Column: email - Samples: [[email protected], [email protected], [email protected], [email protected], [email protected]] - Column: address_1 - Samples: [387 Wellington Ave., 75 W. Berkshire St., 36 Second St., 7607 Sunnyslope Street, 755 Galvin Street] - Column: address_2 - Samples: [Unit 1, None, None, None, None] - Column: city - Samples: [Albuquerque, New York City, New York City, Indianapolis, Indianapolis] - Column: state - Samples: [NM, NY, NY, IN, IN] - Column: zipcode - Samples: [47246, 10040, 10162, 49047, 40852] - Column: district_id - Samples: [18, 1, 1, 5, 5] - Table: district - Column: district_id - Samples: [1, 2, 3, 4, 5] - Column: city - Samples: [New York City, Jacksonville, Columbus, Charlotte, Indianapolis] - Column: state_abbrev - Samples: [NY, FL, OH, NC, IN] - Column: division - Samples: [Middle Atlantic, South Atlantic, East North Central, South Atlantic, East North Central] - Table: events - Column: Date received - Samples: [2014-07-03, 2012-04-12, 2012-04-03, 2012-03-14, 2012-03-05] - Column: Product - Samples: [Bank account or service, Bank account or service, Bank account or service, Credit card, Bank account or service] - Column: Sub-product - Samples: [Checking account, Savings account, Checking account, None, Checking account] - Column: Issue - Samples: [Deposits and withdrawals, Account opening, closing, or management, Account opening, closing, or management, Billing disputes, Account opening, closing, or management] - Column: Sub-issue - Samples: [None, None, None, None, None] - Column: Consumer complaint narrative - Samples: [None, None, None, None, None] - Column: Tags - Samples: [None, None, None, None, None] - Column: Consumer consent provided? - Samples: [N/A, N/A, N/A, N/A, N/A] - Column: Submitted via - Samples: [Email, Email, Email, Email, Email] - Column: Date sent to company - Samples: [2014-07-09, 2012-04-13, 2012-04-03, 2012-03-14, 2012-03-06] - Column: Company response to consumer - Samples: [Closed with explanation, Closed with relief, Closed without relief, Closed with relief, Closed with relief] - Column: Timely response? - Samples: [Yes, Yes, Yes, Yes, Yes] - Column: Consumer disputed? - Samples: [No, No, No, No, No] - Column: Complaint ID - Samples: [CR0922485, CR0057298, CR0043811, CR0035411, CR0030939] - Column: Client_ID - Samples: [C00001925, C00003141, C00000297, C00004275, C00000900] - Table: reviews - Column: Date - Samples: [2017-10-04, 2017-10-02, 2017-08-21, 2017-12-17, 2016-05-27] - Column: Stars - Samples: [5, 5, 5, 5, 5] - Column: Reviews - Samples: [Great job, Eagle National! Each person was professional and helped us ..., Matthew Richardson is professional and helpful. He helped us find the ..., We had a past experience with Eagle National Mortgage and would withou..., We have been dealing with Brad Thomka from the beginning of what start..., I can't express how grateful I am for the support that Zach provided t... (truncated)] - Column: Product - Samples: [Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage] - Column: district_id - Samples: [65, 66, 23, 55, 24]

SELECT DISTINCT T2.Product, T2.Issue FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.age * 100 > ( SELECT AVG(age) * 60 FROM client )

Solve the following sql problem: In reviews of product with 5 stars, what is the percentage of the reviews coming from the division of East North Central? Schema: SCHEMA: - Table: state - Column: StateCode - Samples: [AL, AR, AZ, CA, CO] - Column: State - Samples: [Alabama, Arkansas, Arizona, California, Colorado] - Column: Region - Samples: [South, South, West, West, West] - Table: callcenterlogs - Column: Date received - Samples: [2017-03-27, 2017-03-27, 2017-03-27, 2017-03-23, 2017-03-22] - Column: Complaint ID - Samples: [CR2406263, CR2405641, CR2405629, CR2400594, CR2399607] - Column: rand client - Samples: [C00004587, C00003328, C00001685, C00001945, C00004303] - Column: phonefinal - Samples: [977-806-9726, 322-598-7152, 508-311-5237, 265-394-2727, 206-008-0460] - Column: vru+line - Samples: [AA0103, AA0205, AA0110, AA0113, AA0102] - Column: call_id - Samples: [34536, 34537, 34538, 34540, 34541] - Column: priority - Samples: [0, 0, 2, 2, 1] - Column: type - Samples: [NW, PS, PS, PS, PS] - Column: outcome - Samples: [AGENT, AGENT, AGENT, AGENT, AGENT] - Column: server - Samples: [MICHAL, TOVA, YIFAT, AVNI, STEREN] - Column: ser_start - Samples: [13:34:11, 10:58:22, 13:00:54, 16:18:21, 14:48:22] - Column: ser_exit - Samples: [13:40:23, 11:16:10, 13:13:31, 16:19:40, 14:55:19] - Column: ser_time - Samples: [00:06:12, 00:17:48, 00:12:37, 00:01:19, 00:06:57] - Table: client - Column: client_id - Samples: [C00000001, C00000002, C00000003, C00000004, C00000005] - Column: sex - Samples: [Female, Male, Female, Male, Female] - Column: day - Samples: [13, 4, 9, 1, 3] - Column: month - Samples: [12, 2, 10, 12, 7] - Column: year - Samples: [1990, 1965, 1960, 1976, 1980] - Column: age - Samples: [29, 54, 59, 43, 39] - Column: social - Samples: [926-93-2157, 806-94-5725, 614-70-9100, 580-20-3414, 536-14-5809] - Column: first - Samples: [Emma, Noah, Olivia, Liam, Sophia] - Column: middle - Samples: [Avaya, Everest, Brooklynne, Irvin, Danae] - Column: last - Samples: [Smith, Thompson, Johnson, White, Williams] - Column: phone - Samples: [367-171-6840, 212-423-7734, 212-425-6932, 951-567-8925, 428-265-1568] - Column: email - Samples: [[email protected], [email protected], [email protected], [email protected], [email protected]] - Column: address_1 - Samples: [387 Wellington Ave., 75 W. Berkshire St., 36 Second St., 7607 Sunnyslope Street, 755 Galvin Street] - Column: address_2 - Samples: [Unit 1, None, None, None, None] - Column: city - Samples: [Albuquerque, New York City, New York City, Indianapolis, Indianapolis] - Column: state - Samples: [NM, NY, NY, IN, IN] - Column: zipcode - Samples: [47246, 10040, 10162, 49047, 40852] - Column: district_id - Samples: [18, 1, 1, 5, 5] - Table: district - Column: district_id - Samples: [1, 2, 3, 4, 5] - Column: city - Samples: [New York City, Jacksonville, Columbus, Charlotte, Indianapolis] - Column: state_abbrev - Samples: [NY, FL, OH, NC, IN] - Column: division - Samples: [Middle Atlantic, South Atlantic, East North Central, South Atlantic, East North Central] - Table: events - Column: Date received - Samples: [2014-07-03, 2012-04-12, 2012-04-03, 2012-03-14, 2012-03-05] - Column: Product - Samples: [Bank account or service, Bank account or service, Bank account or service, Credit card, Bank account or service] - Column: Sub-product - Samples: [Checking account, Savings account, Checking account, None, Checking account] - Column: Issue - Samples: [Deposits and withdrawals, Account opening, closing, or management, Account opening, closing, or management, Billing disputes, Account opening, closing, or management] - Column: Sub-issue - Samples: [None, None, None, None, None] - Column: Consumer complaint narrative - Samples: [None, None, None, None, None] - Column: Tags - Samples: [None, None, None, None, None] - Column: Consumer consent provided? - Samples: [N/A, N/A, N/A, N/A, N/A] - Column: Submitted via - Samples: [Email, Email, Email, Email, Email] - Column: Date sent to company - Samples: [2014-07-09, 2012-04-13, 2012-04-03, 2012-03-14, 2012-03-06] - Column: Company response to consumer - Samples: [Closed with explanation, Closed with relief, Closed without relief, Closed with relief, Closed with relief] - Column: Timely response? - Samples: [Yes, Yes, Yes, Yes, Yes] - Column: Consumer disputed? - Samples: [No, No, No, No, No] - Column: Complaint ID - Samples: [CR0922485, CR0057298, CR0043811, CR0035411, CR0030939] - Column: Client_ID - Samples: [C00001925, C00003141, C00000297, C00004275, C00000900] - Table: reviews - Column: Date - Samples: [2017-10-04, 2017-10-02, 2017-08-21, 2017-12-17, 2016-05-27] - Column: Stars - Samples: [5, 5, 5, 5, 5] - Column: Reviews - Samples: [Great job, Eagle National! Each person was professional and helped us ..., Matthew Richardson is professional and helpful. He helped us find the ..., We had a past experience with Eagle National Mortgage and would withou..., We have been dealing with Brad Thomka from the beginning of what start..., I can't express how grateful I am for the support that Zach provided t... (truncated)] - Column: Product - Samples: [Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage, Eagle National Mortgage] - Column: district_id - Samples: [65, 66, 23, 55, 24]

SELECT CAST(SUM(CASE WHEN T1.division = 'East North Central' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.division) FROM district AS T1 INNER JOIN reviews AS T2 ON T1.district_id = T2.district_id WHERE T2.Stars = 5

Solve the following sql problem: Please list the names of the production company of the movie "Four Rooms". Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.company_name FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id INNER JOIN movie AS T3 ON T2.movie_id = T3.movie_id WHERE T3.title = 'Four Rooms'

Solve the following sql problem: How many production companies does the movie "Four Rooms" have? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(CNAME) FROM ( SELECT T1.company_name AS CNAME FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id INNER JOIN movie AS T3 ON T2.movie_id = T3.movie_id WHERE T3.title = 'Four Rooms' )

Solve the following sql problem: Please list the titles of all the movie produced by production company "Universal Pictures". Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.title FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id INNER JOIN movie AS T3 ON T2.movie_id = T3.movie_id WHERE T1.company_name = 'Universal Pictures'

Solve the following sql problem: What is the title of the latest released movie produced by production company "Universal Pictures"? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.title FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id INNER JOIN movie AS T3 ON T2.movie_id = T3.movie_id WHERE T1.company_name = 'Universal Pictures' ORDER BY T3.release_date DESC LIMIT 1

Solve the following sql problem: What is the name of the director of photography of the movie "Pirates of the Caribbean: At World's End"? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.person_name FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T1.title LIKE 'Pirates of the Caribbean: At World%s End' AND T2.job = 'Director of Photography'

Solve the following sql problem: What was the job of Dariusz Wolski in the movie "Pirates of the Caribbean: At World's End"? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T2.job FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T1.title LIKE 'Pirates of the Caribbean: At World%s End' AND T3.person_name = 'Dariusz Wolski'

Solve the following sql problem: Please list the names of all the crew members of the movie "Pirates of the Caribbean: At World's End". Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.person_name FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T1.title LIKE 'Pirates of the Caribbean: At World%s End'

Solve the following sql problem: How many crew members worked as producer in the movie "Pirates of the Caribbean: At World's End"? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(T3.person_id) FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T1.title LIKE 'Pirates of the Caribbean: At World%s End' AND T2.job = 'Producer'

Solve the following sql problem: Please list the names of all the producers in the movie "Pirates of the Caribbean: At World's End". Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.person_name FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T1.title LIKE 'Pirates of the Caribbean: At World%s End' AND T2.job = 'Producer'

Solve the following sql problem: In how many movie does Dariusz Wolski work as the director of photography? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(T2.movie_id) FROM person AS T1 INNER JOIN movie_crew AS T2 ON T1.person_id = T2.person_id WHERE T1.person_name = 'Dariusz Wolski' AND T2.job = 'Director of Photography'

Solve the following sql problem: Among the movie in which Dariusz Wolski works as the director of photography, what is the title of the one with the highest average vote? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.title FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T3.person_name = 'Dariusz Wolski' AND T2.job = 'Director of Photography' ORDER BY T1.vote_average DESC LIMIT 1

Solve the following sql problem: When was the release date of the latest movie in which Dariusz Wolski worked as a crew member? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.release_date FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T3.person_name = 'Dariusz Wolski' ORDER BY T1.release_date DESC LIMIT 1

Solve the following sql problem: Among the movie in which Dariusz Wolski works as the director of photography, what is the percentage of those movie whose vote average is over 5.0? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT CAST(COUNT(CASE WHEN T1.vote_average > 5 THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T1.vote_average) FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T3.person_name = 'Dariusz Wolski' AND T2.job = 'Director of Photography'

Solve the following sql problem: What is the average revenue of the movie in which Dariusz Wolski works as the director of photography? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT CAST(SUM(T1.revenue) AS REAL) / COUNT(T1.movie_id) FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T3.person_name = 'Dariusz Wolski' AND T2.job = 'Director of Photography'

Solve the following sql problem: Give the name of the movie with a revenue of 559852396. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT title FROM movie WHERE revenue = 559852396

Solve the following sql problem: What was David Rubin's job in the movie "Days of Thunder"? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T2.job FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T3.person_name = 'David Rubin' AND T1.title = 'Days of Thunder'

Solve the following sql problem: How many movies were directed by Michael Bay? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(T2.movie_id) FROM person AS T1 INNER JOIN movie_crew AS T2 ON T1.person_id = T2.person_id WHERE T1.person_name = 'Michael Bay' AND T2.job = 'Director'

Solve the following sql problem: Show the total number of keywords of the movie "I Hope They Serve Beer in Hell". Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(T2.keyword_id) FROM movie AS T1 INNER JOIN movie_keywords AS T2 ON T1.movie_id = T2.movie_id WHERE T1.title = 'I Hope They Serve Beer in Hell'

Solve the following sql problem: For the movie "Land of the Dead", who is its director? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.person_name FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T1.title = 'Land of the Dead' AND T2.job = 'Director'

Solve the following sql problem: Tell the number of movies made by Paramount Animation. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(T2.movie_id) FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id WHERE T1.company_name = 'Paramount Animation'

Solve the following sql problem: How many female characters are there in the movie "Spider-Man 3"? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(*) FROM movie AS T1 INNER JOIN movie_cast AS T2 ON T1.movie_id = T2.movie_id INNER JOIN gender AS T3 ON T2.gender_id = T3.gender_id WHERE T1.title = 'Spider-Man 3' AND T3.gender = 'Female'

Solve the following sql problem: Provide the most used keyword in the movies. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.keyword_name FROM keyword AS T1 INNER JOIN movie_keywords AS T2 ON T1.keyword_id = T2.keyword_id GROUP BY T1.keyword_name ORDER BY COUNT(T1.keyword_name) DESC LIMIT 1

Solve the following sql problem: How many producers does the movie "The Amityville Horror" have? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(T2.person_id) FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id WHERE T1.title = 'The Amityville Horror' AND T2.job = 'Producer'

Solve the following sql problem: What is the production company of the movie "Crazy Heart"? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.company_name FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id INNER JOIN movie AS T3 ON T2.movie_id = T3.movie_id WHERE T3.title = 'Crazy Heart'

Solve the following sql problem: Give the number of movies with "saving the world" as the keyword. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(T2.movie_id) FROM keyword AS T1 INNER JOIN movie_keywords AS T2 ON T1.keyword_id = T2.keyword_id WHERE keyword_name = 'saving the world'

Solve the following sql problem: For all the movies which were produced by Cruel and Unusual Films, which one has the most popularity? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.title FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id INNER JOIN movie AS T3 ON T2.movie_id = T3.movie_id WHERE T1.company_name = 'Cruel and Unusual Films' ORDER BY T3.popularity DESC LIMIT 1

Solve the following sql problem: For the movie "Reign of Fire", which department was Marcia Ross in? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T4.department_name FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id INNER JOIN department AS T4 ON T2.department_id = T4.department_id WHERE T3.person_name = 'Marcia Ross' AND T1.title = 'Reign of Fire'

Solve the following sql problem: Calculate the average budget of the movies directed by Jaume Collet-Serra. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT CAST(SUM(T1.budget) AS REAL) / COUNT(T1.movie_id) FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T3.person_name = 'Jaume Collet-Serra' AND T2.job = 'Director'

Solve the following sql problem: What is the percentage of male characters in the movie "Bride Wars"? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT CAST(COUNT(CASE WHEN T3.gender = 'Male' THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T3.gender) FROM movie AS T1 INNER JOIN movie_cast AS T2 ON T1.movie_id = T2.movie_id INNER JOIN gender AS T3 ON T2.gender_id = T3.gender_id WHERE T1.title = 'Bride Wars'

Solve the following sql problem: What is the title of the movie that was made with the most money and resources? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT title FROM movie ORDER BY budget DESC LIMIT 1

Solve the following sql problem: How many movies have made at least 1 Billion at the box office? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(movie_id) FROM movie WHERE revenue > 1000000000

Solve the following sql problem: When was the first movie released? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT MIN(release_date) FROM movie WHERE movie_status = 'Released'

Solve the following sql problem: How many crew are named John Young? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(person_id) FROM person WHERE person_name = 'John Young'

Solve the following sql problem: Provide the title of the movie that is most-liked by a large number of people. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT title FROM movie ORDER BY popularity DESC LIMIT 1

Solve the following sql problem: Who is the person associated with the crew id 1325273? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT person_name FROM person WHERE person_id = 1325273

Solve the following sql problem: What is the name of the production company that made the most movies? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.company_name FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id GROUP BY T1.company_id ORDER BY COUNT(T2.movie_id) DESC LIMIT 1

Solve the following sql problem: Who played Captain Jack Sparrow in all of the Pirates of the Caribbean movies? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT DISTINCT T3.person_name FROM movie AS T1 INNER JOIN movie_cast AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T2.character_name = 'Captain Jack Sparrow' AND T1.title LIKE 'Pirates of the Caribbean%'

Solve the following sql problem: What is Walt Disney Pictures' most popular movie? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.title FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id INNER JOIN movie AS T3 ON T2.movie_id = T3.movie_id WHERE T1.company_name = 'Walt Disney Pictures' ORDER BY T3.popularity DESC LIMIT 1

Solve the following sql problem: How many movies did Universal Studios release? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(T2.movie_id) FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id WHERE T1.company_name = 'Universal Studios'

Solve the following sql problem: Which production company produced the movie that made the most money at the box office? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.company_name FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id INNER JOIN movie AS T3 ON T2.movie_id = T3.movie_id GROUP BY T1.company_id ORDER BY SUM(T3.revenue) DESC LIMIT 1

Solve the following sql problem: How many female crews are in the movie "Mr. Smith Goes to Washington"? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(T3.gender) FROM movie AS T1 INNER JOIN movie_cast AS T2 ON T1.movie_id = T2.movie_id INNER JOIN gender AS T3 ON T2.gender_id = T3.gender_id WHERE T1.title = 'Mr. Smith Goes to Washington' AND T3.gender = 'Female'

Solve the following sql problem: List the names of the production companies that made at least 200 movies. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.company_name FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id GROUP BY T1.company_id HAVING COUNT(T2.movie_id) > 200

Solve the following sql problem: How many movies did Harrison Ford appear in total? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(T2.movie_id) FROM person AS T1 INNER JOIN movie_cast AS T2 ON T1.person_id = T2.person_id WHERE T1.person_name = 'Harrison Ford'

Solve the following sql problem: What is the title of Jamie Foxx's most recent movie? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.title FROM movie AS T1 INNER JOIN movie_cast AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T3.person_name = 'Jamie Foxx' ORDER BY T1.release_date DESC LIMIT 1

Solve the following sql problem: How many movies released in 1995 did Quentin Tarantino appear in? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(T1.movie_id) FROM movie AS T1 INNER JOIN movie_cast AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T3.person_name = 'Quentin Tarantino' AND CAST(STRFTIME('%Y', T1.release_date) AS INT) = 1995

Solve the following sql problem: What is the title of the first crime movie ever released? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.title FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN genre AS T3 ON T2.genre_id = T3.genre_id WHERE T3.genre_name = 'Crime' ORDER BY T1.release_date LIMIT 1

Solve the following sql problem: How many horror movies are there? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(T1.movie_id) FROM movie_genres AS T1 INNER JOIN genre AS T2 ON T1.genre_id = T2.genre_id WHERE T2.genre_name = 'Horror'

Solve the following sql problem: List the person IDs of the second film editors in Movie No. 12. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT person_id FROM movie_crew WHERE movie_id = 12 AND job = 'Second Film Editor'

Solve the following sql problem: How many animators does Movie No. 129 have? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(movie_id) FROM movie_crew WHERE movie_id = 129 AND job = 'Animation'

Solve the following sql problem: In Movie No. 19, how many people are there in Department No. 7? Please give me their job. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(DISTINCT job) FROM movie_crew WHERE movie_id = 19 AND department_id = 7

Solve the following sql problem: Write the person ID and character name of casts between order numbers 1 and 10 in Movie No. 285. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT person_id, character_name FROM movie_cast WHERE movie_id = 285 AND cast_order BETWEEN 1 AND 10

Solve the following sql problem: How many times did Bob Peterson appear in the movie credits? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(T2.movie_id) FROM person AS T1 INNER JOIN movie_cast AS T2 ON T1.person_id = T2.person_id WHERE T1.person_name = 'Bob Peterson'

Solve the following sql problem: Tally the movie ID and character name in the movie starring Jim Carrey. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T2.movie_id, T2.character_name FROM person AS T1 INNER JOIN movie_cast AS T2 ON T1.person_id = T2.person_id WHERE T1.person_name = 'Jim Carrey'

Solve the following sql problem: Give the names of the female cast in Movie No. 1865. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T2.person_name FROM movie_cast AS T1 INNER JOIN person AS T2 ON T1.person_id = T2.person_id INNER JOIN gender AS T3 ON T1.gender_id = T3.gender_id WHERE T1.movie_id = 1865 AND T3.gender = 'Female'

Solve the following sql problem: Write me the titles of the movies starring Jim Carrey. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.title FROM movie AS T1 INNER JOIN movie_cast AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T3.person_name = 'Jim Carrey'

Solve the following sql problem: List the director's name of the movies released between 1/01/1916 and 12/31/1925. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T2.person_name FROM movie_cast AS T1 INNER JOIN person AS T2 ON T1.person_id = T2.person_id INNER JOIN movie AS T3 ON T1.movie_id = T3.movie_id INNER JOIN movie_crew AS T4 ON T1.movie_id = T4.movie_id WHERE T4.job = 'Director' AND T3.release_date BETWEEN '1916-01-01' AND '1925-12-31'

Solve the following sql problem: How many films released between 1/2/1990 and 12/30/2000 starred Uma Thurman? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(T1.movie_id) FROM movie AS T1 INNER JOIN movie_cast AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T3.person_name = 'Uma Thurman' AND T1.release_date BETWEEN '1990-01-01' AND '2000-12-31'

Solve the following sql problem: Write the titles of horror films with a vote average of more than 7. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.title FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN genre AS T3 ON T2.genre_id = T3.genre_id WHERE T3.genre_name = 'Horror' AND vote_average > 7

Solve the following sql problem: Give the genre and popularity of movies whose revenue is at least 120,000,000 between 2012 and 2015. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.genre_name, T1.popularity FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN genre AS T3 ON T2.genre_id = T3.genre_id WHERE T1.revenue > 120000000 AND T1.release_date BETWEEN '2012-01-01' AND '2015-12-31'

Solve the following sql problem: How many Indian movies between 1/2/1990 and 12/30/2003 have revenue of more than 75,000,000 and popularity of no less than 20? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT COUNT(T2.movie_id) FROM movie AS T1 INNER JOIN production_COUNTry AS T2 ON T1.movie_id = T2.movie_id WHERE T1.revenue > 75000000 AND T1.popularity >= 20 AND T1.release_date BETWEEN '1990-01-01' AND '2003-12-31'

Solve the following sql problem: What is the title of the highest-budget film to date? Please include the revenue and name the country. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.title, T1.revenue, T3.COUNTry_name FROM movie AS T1 INNER JOIN production_COUNTry AS T2 ON T1.movie_id = T2.movie_id INNER JOIN COUNTry AS T3 ON T2.COUNTry_id = T3.COUNTry_id ORDER BY T1.budget DESC LIMIT 1

Solve the following sql problem: List the title of movies in Latin released between 1/01/1990 and 12/31/1995. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.title FROM movie AS T1 INNER JOIN movie_languages AS T2 ON T1.movie_id = T2.movie_id INNER JOIN language AS T3 ON T2.language_id = T3.language_id WHERE T3.language_name = 'Latin' AND T1.release_date BETWEEN '1990-01-01' AND '1995-12-31'

Solve the following sql problem: What is the average revenue of American movies in 2006? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT AVG(T1.revenue) FROM movie AS T1 INNER JOIN production_COUNTry AS T2 ON T1.movie_id = T2.movie_id INNER JOIN COUNTry AS T3 ON T2.COUNTry_id = T3.COUNTry_id WHERE T3.COUNTry_name = 'United States of America' AND CAST(STRFTIME('%Y', T1.release_date) AS INT) = 2006

Solve the following sql problem: Calculate the 2016 gap between the average revenue for Indian and American films. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT AVG(CASE WHEN T3.COUNTry_name = 'United States of America' THEN T1.revenue END) - AVG(CASE WHEN T3.COUNTry_name = 'India' THEN T1.revenue END) AS CALCULATE FROM movie AS T1 INNER JOIN production_COUNTry AS T2 ON T1.movie_id = T2.movie_id INNER JOIN COUNTry AS T3 ON T2.COUNTry_id = T3.COUNTry_id WHERE CAST(STRFTIME('%Y', T1.release_date) AS INT) = 2016

Solve the following sql problem: What is the percentage of romance films among films produced in India in 2015? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT CAST(COUNT(CASE WHEN T4.genre_name = 'Romance' THEN T1.movie_id ELSE NULL END) AS REAL) * 100 / COUNT(T1.movie_id) FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN production_COUNTry AS T3 ON T1.movie_id = T3.movie_id INNER JOIN genre AS T4 ON T2.genre_id = T4.genre_id INNER JOIN COUNTry AS T5 ON T3.COUNTry_id = T5.COUNTry_id WHERE T5.COUNTry_name = 'India' AND T1.release_date BETWEEN '2015-01-01' AND '2015-12-31'

Solve the following sql problem: Which actor plays Optimus Prime? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT DISTINCT T1.person_name FROM person AS T1 INNER JOIN movie_cast AS T2 ON T1.person_id = T2.person_id WHERE T2.character_name = 'Optimus Prime (voice)'

Solve the following sql problem: What is the gender of the character 'USAF Master Sgt. Epps?' Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T2.gender FROM movie_cast AS T1 INNER JOIN gender AS T2 ON T1.gender_id = T2.gender_id WHERE T1.character_name = 'USAF Master Sgt. Epps'

Solve the following sql problem: List all companies who worked in the movie 'Ultramarines: A Warhammer 40,000 Movie.' Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.company_name FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id INNER JOIN movie AS T3 ON T2.movie_id = T3.movie_id WHERE T3.title = 'Ultramarines: A Warhammer 40,000 Movie'

Solve the following sql problem: Which movie did the company 'Radiant Film GmbH' work on? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.title FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id INNER JOIN movie AS T3 ON T2.movie_id = T3.movie_id WHERE T1.company_name = 'Radiant Film GmbH'

Solve the following sql problem: What are the genres of Sky Captain and the World of Tomorrow? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.genre_name FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN genre AS T3 ON T2.genre_id = T3.genre_id WHERE T1.title = 'Sky Captain and the World of Tomorrow'

Solve the following sql problem: Write all the keywords belonging to the movie 'Sky Captain and the World of Tomorrow.' Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.keyword_name FROM movie AS T1 INNER JOIN movie_keywords AS T2 ON T1.movie_id = T2.movie_id INNER JOIN keyword AS T3 ON T2.keyword_id = T3.keyword_id WHERE T1.title = 'Sky Captain and the World of Tomorrow'

Solve the following sql problem: The movie 'Gojira ni-sen mireniamu' is from which country? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.COUNTry_name FROM movie AS T1 INNER JOIN production_COUNTry AS T2 ON T1.movie_id = T2.movie_id INNER JOIN COUNTry AS T3 ON T2.COUNTry_id = T3.COUNTry_id WHERE T1.title = 'Gojira ni-sen mireniamu'

Solve the following sql problem: Which movie has the keyword 'extremis?' Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.title FROM movie AS T1 INNER JOIN movie_keywords AS T2 ON T1.movie_id = T2.movie_id INNER JOIN keyword AS T3 ON T2.keyword_id = T3.keyword_id WHERE T3.keyword_name = 'extremis'

Solve the following sql problem: List 10 movie titles that were produced in France. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.title FROM movie AS T1 INNER JOIN production_COUNTry AS T2 ON T1.movie_id = T2.movie_id INNER JOIN COUNTry AS T3 ON T2.COUNTry_id = T3.COUNTry_id WHERE T3.COUNTry_name = 'France' LIMIT 10

Solve the following sql problem: Who is the director for the movie 'Transformers?' Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.person_name FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T1.title = 'Transformers' AND T2.job = 'Director'

Solve the following sql problem: List 10 crews alongside their jobs who worked on the movie 'Mad Max: Fury Road.' Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.person_name FROM movie AS T1 INNER JOIN movie_crew AS T2 ON T1.movie_id = T2.movie_id INNER JOIN person AS T3 ON T2.person_id = T3.person_id WHERE T1.title = 'Mad Max: Fury Road' LIMIT 10

Solve the following sql problem: What percentage of movies that came from Japan belong in the 'animation' genre? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT CAST(COUNT(CASE WHEN T4.genre_name = 'Animation' THEN T1.movie_id ELSE NULL END) AS REAL) * 100 / COUNT(T1.movie_id) FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN production_COUNTry AS T3 ON T1.movie_id = T3.movie_id INNER JOIN genre AS T4 ON T2.genre_id = T4.genre_id INNER JOIN COUNTry AS T5 ON T3.COUNTry_id = T5.COUNTry_id WHERE T5.COUNTry_name = 'Japan'

Solve the following sql problem: What is the ratio between male and female cast members of the movie 'Iron Man?' Count how many have unspecified genders. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT CAST(COUNT(CASE WHEN T3.gender = 'Male' THEN 1 ELSE NULL END) AS REAL) / COUNT(CASE WHEN T3.gender = 'Female' THEN 1 ELSE NULL END) AS RATIO , COUNT(CASE WHEN T3.gender = 'Unspecified' THEN 1 ELSE NULL END) AS UNGENDERS FROM movie AS T1 INNER JOIN movie_cast AS T2 ON T1.movie_id = T2.movie_id INNER JOIN gender AS T3 ON T2.gender_id = T3.gender_id WHERE T1.title = 'Iron Man'

Solve the following sql problem: List down five movie titles that were released before 2000. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT title FROM movie WHERE CAST(STRFTIME('%Y', release_date) AS INT) < 2000 LIMIT 5

Solve the following sql problem: What is the keyword ID of the movie with the title of "Sin City"? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T2.keyword_id FROM movie AS T1 INNER JOIN movie_keywords AS T2 ON T1.movie_id = T2.movie_id WHERE T1.title = 'Sin City'

Solve the following sql problem: Look for the movie title with the keyword of "angel". Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.title FROM movie AS T1 INNER JOIN movie_keywords AS T2 ON T1.movie_id = T2.movie_id INNER JOIN keyword AS T3 ON T2.keyword_id = T3.keyword_id WHERE T3.keyword_name = 'angel'

Solve the following sql problem: Which keywords belong to the movie titles with the highest popularity? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.keyword_name FROM movie AS T1 INNER JOIN movie_keywords AS T2 ON T1.movie_id = T2.movie_id INNER JOIN keyword AS T3 ON T2.keyword_id = T3.keyword_id ORDER BY T1.popularity DESC LIMIT 1

Solve the following sql problem: Provide the genre ID of the movie with the title of "The Dark Knight". Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T2.genre_id FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id WHERE T1.title = 'The Dark Knight'

Solve the following sql problem: List down the movie titles within the genre of thriller. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.title FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN genre AS T3 ON T2.genre_id = T3.genre_id WHERE T3.genre_name = 'Thriller'

Solve the following sql problem: Write down five rumoured movie titles within the genre of Drama. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.title FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN genre AS T3 ON T2.genre_id = T3.genre_id WHERE T1.movie_status = 'Rumored' AND T3.genre_name = 'Drama' LIMIT 5

Solve the following sql problem: What is the genre of the movie title with the lowest revenue generated? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.genre_name FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN genre AS T3 ON T2.genre_id = T3.genre_id ORDER BY T1.revenue LIMIT 1

Solve the following sql problem: State the genre of the movie title with a runtime of only 14 minutes. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.genre_name FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN genre AS T3 ON T2.genre_id = T3.genre_id WHERE T1.runtime = 14

Solve the following sql problem: What is the genre of the movie title which was well-received by the audiences but made the lowest revenue? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.genre_name FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN genre AS T3 ON T2.genre_id = T3.genre_id ORDER BY T1.vote_average DESC, T1.revenue LIMIT 1

Solve the following sql problem: Provide the genre of a movie title with a tagline of "A long time ago in a galaxy far, far away…". Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T3.genre_name FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN genre AS T3 ON T3.genre_id = T2.genre_id WHERE T1.tagline = 'A long time ago in a galaxy far, far away...'

Solve the following sql problem: What is the country ID of the movie with the title of "Pirates of the Caribbean: Dead Man's Chest"? Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T2.COUNTry_id FROM movie AS T1 INNER JOIN production_COUNTry AS T2 ON T1.movie_id = T2.movie_id WHERE T1.title LIKE 'Pirates of the Caribbean: Dead Man%s Chest'

Solve the following sql problem: List down the movie titles that were produced in Canada. Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT T1.title FROM movie AS T1 INNER JOIN production_COUNTry AS T2 ON T1.movie_id = T2.movie_id INNER JOIN COUNTry AS T3 ON T2.COUNTry_id = T3.COUNTry_id WHERE T3.COUNTry_name = 'Canada'

Solve the following sql problem: Accumulate the budget of the movie titles with the keyword of "video game". Schema: SCHEMA: - Table: country - Column: country_id - Samples: [128, 129, 130, 131, 132] - Column: country_iso_code - Samples: [AE, AF, AO, AR, AT] - Column: country_name - Samples: [United Arab Emirates, Afghanistan, Angola, Argentina, Austria] - Table: department - Column: department_id - Samples: [1, 2, 3, 4, 5] - Column: department_name - Samples: [Camera, Directing, Production, Writing, Editing] - Table: gender - Column: gender_id - Samples: [0, 1, 2] - Column: gender - Samples: [Unspecified, Female, Male] - Table: genre - Column: genre_id - Samples: [12, 14, 16, 18, 27] - Column: genre_name - Samples: [Adventure, Fantasy, Animation, Drama, Horror] - Table: keyword - Column: keyword_id - Samples: [30, 65, 74, 75, 83] - Column: keyword_name - Samples: [individual, holiday, germany, gunslinger, saving the world] - Table: language - Column: language_id - Samples: [24574, 24575, 24576, 24577, 24578] - Column: language_code - Samples: [en, sv, de, xx, ja] - Column: language_name - Samples: [English, svenska, Deutsch, No Language, u65e5u672cu8a9e] - Table: language_role - Column: role_id - Samples: [1, 2] - Column: language_role - Samples: [Original, Spoken] - Table: movie - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: title - Samples: [Four Rooms, Star Wars, Finding Nemo, Forrest Gump, American Beauty] - Column: budget - Samples: [4000000, 11000000, 94000000, 55000000, 15000000] - Column: homepage - Samples: [, http://www.starwars.com/films/star-wars-episode-iv-a-new-hope, http://movies.disney.com/finding-nemo, , http://www.dreamworks.com/ab/] - Column: overview - Samples: [It's Ted the Bellhop's first night on the job...and the hotel's very u..., Princess Leia is captured and held hostage by the evil Imperial forces..., Nemo, an adventurous young clownfish, is unexpectedly taken from his G..., A man with a low IQ has accomplished great things in his life and been..., Lester Burnham, a depressed suburban father in a mid-life crisis, deci... (truncated)] - Column: popularity - Samples: [22.87623, 126.393695, 85.688789, 138.133331, 80.878605] - Column: release_date - Samples: [1995-12-09, 1977-05-25, 2003-05-30, 1994-07-06, 1999-09-15] - Column: revenue - Samples: [4300000, 775398007, 940335536, 677945399, 356296601] - Column: runtime - Samples: [98, 121, 100, 142, 122] - Column: movie_status - Samples: [Released, Released, Released, Released, Released] - Column: tagline - Samples: [Twelve outrageous guests. Four scandalous requests. And one lone bellh..., A long time ago in a galaxy far, far away..., There are 3.7 trillion fish in the ocean, they're looking for one., The world will never be the same, once you've seen it through the eyes..., Look closer. (truncated)] - Column: vote_average - Samples: [6.5, 8.1, 7.6, 8.2, 7.9] - Column: vote_count - Samples: [530, 6624, 6122, 7927, 3313] - Table: movie_genres - Column: movie_id - Samples: [5, 5, 11, 11, 11] - Column: genre_id - Samples: [35, 80, 12, 28, 878] - Table: movie_languages - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: language_id - Samples: [24574, 24574, 24574, 24574, 24574] - Column: language_role_id - Samples: [2, 2, 2, 2, 2] - Table: person - Column: person_id - Samples: [1, 2, 3, 4, 5] - Column: person_name - Samples: [George Lucas, Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing] - Table: movie_crew - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [120, 1704, 770, 1705, 1706] - Column: department_id - Samples: [1, 2, 3, 4, 4] - Column: job - Samples: [Director of Photography, Director, Producer, Screenplay, Screenplay] - Table: production_company - Column: company_id - Samples: [1, 2, 3, 4, 5] - Column: company_name - Samples: [Lucasfilm, Walt Disney Pictures, Pixar Animation Studios, Paramount Pictures, Columbia Pictures] - Table: production_country - Column: movie_id - Samples: [5, 11, 12, 13, 14] - Column: country_id - Samples: [214, 214, 214, 214, 214] - Table: movie_cast - Column: movie_id - Samples: [285, 285, 285, 285, 285] - Column: person_id - Samples: [85, 114, 116, 1640, 1619] - Column: character_name - Samples: [Captain Jack Sparrow, Will Turner, Elizabeth Swann, William Bootstrap Bill Turner, Captain Sao Feng] - Column: gender_id - Samples: [2, 2, 1, 2, 2] - Column: cast_order - Samples: [0, 1, 2, 3, 4] - Table: movie_keywords - Column: movie_id - Samples: [5, 5, 5, 5, 5] - Column: keyword_id - Samples: [612, 613, 616, 622, 922] - Table: movie_company - Column: movie_id - Samples: [5, 5, 11, 11, 12] - Column: company_id - Samples: [14, 59, 1, 306, 3]

SELECT SUM(T1.budget) FROM movie AS T1 INNER JOIN movie_keywords AS T2 ON T1.movie_id = T2.movie_id INNER JOIN keyword AS T3 ON T2.keyword_id = T3.keyword_id WHERE T3.keyword_name = 'video game'