remove files

README.md

@@ -1,50 +1,13 @@
 ---
 configs:
-- config_name: idiom-detection-task
+- config_name: Idioms Detection Task
   data_files:
   - split: test
-    path: "idiom_detection_task.csv"
-- config_name: metaphor-detection-task
+    path: "idiom_understanding_task.csv"
+- config_name: Metaphors Detection Task
   data_files:
   - split: test
-    path: "metaphor_detection_task.csv"
-- config_name: simile-detection-task
-  data_files:
-  - split: test
-    path: "simile_detection_task.csv"
-- config_name: open-simile-detection-task
-  data_files:
-  - split: test
-    path: "open_simile_detection_task.csv"
-- config_name: idiom-retrieval-task
-  data_files:
-  - split: test
-    path: "idiom_retrieval_task.csv"
-- config_name: metaphor-retrieval-task
-  data_files:
-  - split: test
-    path: "metaphor_retrieval_task.csv"
-- config_name: simile-retrieval-task
-  data_files:
-  - split: test
-    path: "simile_retrieval_task.csv"
-- config_name: open-simile-retrieval-task
-  data_files:
-  - split: test
-    path: "open_simile_retrieval_task.csv"
-- config_name: idioms-dataset
-  data_files:
-  - split: dataset
-    path: "idioms_dataset.csv"
-- config_name: similes-dataset
-  data_files:
-  - split: dataset
-    path: "similes_dataset.csv"
-- config_name: metaphors-dataset
-  data_files:
-  - split: dataset
-    path: "metaphors_dataset.csv"
-
+    path: "metaphor_understanding_task.csv"
 license: cc-by-4.0
 language:
 - en
@@ -98,8 +61,8 @@ [email protected]; [email protected]
 
 https://irfl-dataset.github.io/leaderboard 
 
-### Colab notebook for IRFL evaluation
-https://colab.research.google.com/drive/1RfcUhBTHvREx5X7TMY5UAgMYX8NMKy7u?usp=sharing
+### Colab notebook code for IRFL evaluation
+https://colab.research.google.com/drive/1zbW7R8Cn9sXICV3x_FGKjKIKu8GCrCme?usp=sharing
 
 ### Languages
 
@@ -109,40 +72,39 @@ English.
 
 ### Data Fields
 ★ - refers to idiom-only fields
-⁺₊ - refers to metaphor-only fields
 
-Multimodal Figurative Language Detection task
+Detection task
 - query (★): the idiom definition the answer image originated from.
 - distractors: the distractor images
 - answer: the correct image 
 - figurative_type: idiom | metaphor | simile
-- type: the correct image type (Figurative or Figurative+Literal).
+- images_metadata: the metadata of the distractors and asnwer images. 
+- type: the correct image type (Figurative or Figurative Literal).
 - definition (★): list of all the definitions of the idiom
 - phrase: the figurative phrase.
 
-Multimodal Figurative Language Retrieval task
-- type: the rival categories FvsPL (Figurative images vs. Partial Literal) or FLvsPL (Figurative+Literal images vs. Partial Literal)
+Retrieval task
+- type: the rival categories FvsPO (Figurative images vs. Partial Objects) or FLvsPO (Figurative Literal images vs. Partial Objects)
 - figurative_type: idiom | metaphor | simile
-- images_metadata: the metadata of the distractors and answer images. 
-- first_category: the first category images (Figurative images if FvsPL, Figurative Literal images if FLvsPL)
-- second_category: the second category images (Partial Literal)
+- first_category: the first category images (Figurative images if FvsPO, Figurative Literal images if FLvsPO)
+- second_category: the second category images (Partial Objects)
 - definition (★): list of all the definitions of the idiom
-- theme (⁺₊): the theme of the partial literal distractor, for example, for the metaphor heart of gold, an image of a "gold bar" and an image of a "human heart" will have different theme value
 - phrase: the figurative phrase.
 
 The idioms, metaphor, and similes datasets contain all the figurative phrases, annotated images, and corresponding metadata. <br/>
 
+
 ## Dataset Collection
-Using an automatic pipeline we created, we collected figurative and literal images for textual idioms, metaphors, and similes. We annotated the relations between these images and the figurative phrase they originated from.
+We collected figurative and literal images for textual idioms, metaphors, and similes using an automatic pipeline we created. We annotated the relations between these images and the figurative phrase they originated from.
 
 #### Annotation process
 
 We paid Amazon Mechanical Turk Workers to annotate the relation between each image and phrase (Figurative vs. Literal).  
 
 ## Considerations for Using the Data
-- Idioms: Annotated by five crowdworkers with rigorous qualifications and training.
-- Metaphors and Similes: Annotated by three expert team members.
-- Detection and Ranking Tasks: Annotated by three crowdworkers not involved in prior IRFL annotations.
+- Idioms: Annotated by crowdworkers with rigorous qualifications and training.
+- Metaphors and Similes: Annotated by expert team members.
+- Detection and Ranking Tasks: Annotated by crowdworkers not involved in prior IRFL annotations.
 
 ### Licensing Information
 

idioms_dataset.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:29cb0c064ad8b87535d8e120f6aee17956326b0fc7494b8f92e4a8c49436385d
+size 5630459