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--- |
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annotations_creators: |
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- crowdsourced |
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language_creators: |
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- crowdsourced |
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language: |
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- en |
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license: |
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- cc-by-4.0 |
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multilinguality: |
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- monolingual |
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size_categories: |
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- 10K<n<100K |
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source_datasets: |
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- original |
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task_categories: |
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- text-generation |
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- fill-mask |
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task_ids: |
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- dialogue-modeling |
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paperswithcode_id: null |
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pretty_name: taskmaster3 |
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dataset_info: |
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features: |
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- name: conversation_id |
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dtype: string |
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- name: vertical |
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dtype: string |
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- name: instructions |
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dtype: string |
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- name: scenario |
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dtype: string |
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- name: utterances |
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list: |
|
- name: index |
|
dtype: int32 |
|
- name: speaker |
|
dtype: string |
|
- name: text |
|
dtype: string |
|
- name: apis |
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list: |
|
- name: name |
|
dtype: string |
|
- name: index |
|
dtype: int32 |
|
- name: args |
|
list: |
|
- name: arg_name |
|
dtype: string |
|
- name: arg_value |
|
dtype: string |
|
- name: response |
|
list: |
|
- name: response_name |
|
dtype: string |
|
- name: response_value |
|
dtype: string |
|
- name: segments |
|
list: |
|
- name: start_index |
|
dtype: int32 |
|
- name: end_index |
|
dtype: int32 |
|
- name: text |
|
dtype: string |
|
- name: annotations |
|
list: |
|
- name: name |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 143609327 |
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num_examples: 23757 |
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download_size: 313402141 |
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dataset_size: 143609327 |
|
--- |
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|
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# Dataset Card for taskmaster3 |
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|
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## Table of Contents |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Dataset Creation](#dataset-creation) |
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- [Curation Rationale](#curation-rationale) |
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- [Source Data](#source-data) |
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- [Annotations](#annotations) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Social Impact of Dataset](#social-impact-of-dataset) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Other Known Limitations](#other-known-limitations) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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- [Contributions](#contributions) |
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|
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## Dataset Description |
|
|
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- **Homepage:** [Taskmaster](https://research.google/tools/datasets/taskmaster-1/) |
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- **Repository:** [GitHub](https://github.com/google-research-datasets/Taskmaster/tree/master/TM-3-2020) |
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- **Paper:** [Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset](https://arxiv.org/abs/1909.05358) |
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- **Leaderboard:** N/A |
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- **Point of Contact:** [Taskmaster Googlegroup]([email protected]) |
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|
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### Dataset Summary |
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|
|
Taskmaster is dataset for goal oriented conversations. The Taskmaster-3 dataset consists of 23,757 movie ticketing dialogs. |
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By "movie ticketing" we mean conversations where the customer's goal is to purchase tickets after deciding |
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on theater, time, movie name, number of tickets, and date, or opt out of the transaction. This collection |
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was created using the "self-dialog" method. This means a single, crowd-sourced worker is |
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paid to create a conversation writing turns for both speakers, i.e. the customer and the ticketing agent. |
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|
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### Supported Tasks and Leaderboards |
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|
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[More Information Needed] |
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|
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### Languages |
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|
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The dataset is in English language. |
|
|
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## Dataset Structure |
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|
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### Data Instances |
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|
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A typical example looks like this |
|
|
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``` |
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{ |
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"conversation_id": "dlg-ddee80da-9ffa-4773-9ce7-f73f727cb79c", |
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"instructions": "SCENARIO: Pretend you’re *using a digital assistant to purchase tickets for a movie currently showing in theaters*. ...", |
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"scenario": "4 exchanges with 1 error and predefined variables", |
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"utterances": [ |
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{ |
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"apis": [], |
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"index": 0, |
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"segments": [ |
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{ |
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"annotations": [ |
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{ |
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"name": "num.tickets" |
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} |
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], |
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"end_index": 21, |
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"start_index": 20, |
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"text": "2" |
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}, |
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{ |
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"annotations": [ |
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{ |
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"name": "name.movie" |
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} |
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], |
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"end_index": 42, |
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"start_index": 37, |
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"text": "Mulan" |
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} |
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], |
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"speaker": "user", |
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"text": "I would like to buy 2 tickets to see Mulan." |
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}, |
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{ |
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"index": 6, |
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"segments": [], |
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"speaker": "user", |
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"text": "Yes.", |
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"apis": [ |
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{ |
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"args": [ |
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{ |
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"arg_name": "name.movie", |
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"arg_value": "Mulan" |
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}, |
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{ |
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"arg_name": "name.theater", |
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"arg_value": "Mountain AMC 16" |
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} |
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], |
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"index": 6, |
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"name": "book_tickets", |
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"response": [ |
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{ |
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"response_name": "status", |
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"response_value": "success" |
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} |
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] |
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} |
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] |
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} |
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], |
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"vertical": "Movie Tickets" |
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} |
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``` |
|
|
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### Data Fields |
|
|
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Each conversation in the data file has the following structure: |
|
|
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- `conversation_id`: A universally unique identifier with the prefix 'dlg-'. The ID has no meaning. |
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- `utterances`: A list of utterances that make up the conversation. |
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- `instructions`: Instructions for the crowdsourced worker used in creating the conversation. |
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- `vertical`: In this dataset the vertical for all dialogs is "Movie Tickets". |
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- `scenario`: This is the title of the instructions for each dialog. |
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|
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Each utterance has the following fields: |
|
|
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- `index`: A 0-based index indicating the order of the utterances in the conversation. |
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- `speaker`: Either USER or ASSISTANT, indicating which role generated this utterance. |
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- `text`: The raw text of the utterance. In case of self dialogs (one_person_dialogs), this is written by the crowdsourced worker. In case of the WOz dialogs, 'ASSISTANT' turns are written and 'USER' turns are transcribed from the spoken recordings of crowdsourced workers. |
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- `segments`: A list of various text spans with semantic annotations. |
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- `apis`: An array of API invocations made during the utterance. |
|
|
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Each API has the following structure: |
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|
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- `name`: The name of the API invoked (e.g. find_movies). |
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- `index`: The index of the parent utterance. |
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- `args`: A `list` of `dict` with keys `arg_name` and `arg_value` which represent the name of the argument and the value for the argument respectively. |
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- `response`: A `list` of `dict`s with keys `response_name` and `response_value` which represent the name of the response and the value for the response respectively. |
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|
|
Each segment has the following fields: |
|
|
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- `start_index`: The position of the start of the annotation in the utterance text. |
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- `end_index`: The position of the end of the annotation in the utterance text. |
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- `text`: The raw text that has been annotated. |
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- `annotations`: A list of annotation details for this segment. |
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|
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Each annotation has a single field: |
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|
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- `name`: The annotation name. |
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|
|
|
|
|
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### Data Splits |
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|
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There are no deafults splits for all the config. The below table lists the number of examples in each config. |
|
|
|
| | Train | |
|
|-------------------|--------| |
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| n_instances | 23757 | |
|
|
|
|
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## Dataset Creation |
|
|
|
### Curation Rationale |
|
|
|
[More Information Needed] |
|
|
|
### Source Data |
|
|
|
[More Information Needed] |
|
|
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#### Initial Data Collection and Normalization |
|
|
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[More Information Needed] |
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|
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#### Who are the source language producers? |
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|
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[More Information Needed] |
|
|
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### Annotations |
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|
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[More Information Needed] |
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|
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#### Annotation process |
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|
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[More Information Needed] |
|
|
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#### Who are the annotators? |
|
|
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[More Information Needed] |
|
|
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### Personal and Sensitive Information |
|
|
|
[More Information Needed] |
|
|
|
## Considerations for Using the Data |
|
|
|
### Social Impact of Dataset |
|
|
|
[More Information Needed] |
|
|
|
### Discussion of Biases |
|
|
|
[More Information Needed] |
|
|
|
### Other Known Limitations |
|
|
|
[More Information Needed] |
|
|
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## Additional Information |
|
|
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### Dataset Curators |
|
|
|
[More Information Needed] |
|
|
|
### Licensing Information |
|
|
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The dataset is licensed under `Creative Commons Attribution 4.0 License` |
|
|
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### Citation Information |
|
|
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[More Information Needed] |
|
``` |
|
@inproceedings{48484, |
|
title = {Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset}, |
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author = {Bill Byrne and Karthik Krishnamoorthi and Chinnadhurai Sankar and Arvind Neelakantan and Daniel Duckworth and Semih Yavuz and Ben Goodrich and Amit Dubey and Kyu-Young Kim and Andy Cedilnik}, |
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year = {2019} |
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} |
|
``` |
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### Contributions |
|
|
|
Thanks to [@patil-suraj](https://github.com/patil-suraj) for adding this dataset. |
