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Dataset Card for "story_cloze"
Dataset Summary
Story Cloze Test' is a new commonsense reasoning framework for evaluating story understanding, story generation, and script learning.This test requires a system to choose the correct ending to a four-sentence story.
Supported Tasks and Leaderboards
commonsense reasoning
Languages
English
Dataset Structure
Data Instances
- Size of downloaded dataset files: 2.13 MB
 - Size of the generated dataset: 2.13 MB
 - Total amount of disk used: 2.15 MB
 
An example of 'train' looks as follows.
{'answer_right_ending': 1,
 'input_sentence_1': 'Rick grew up in a troubled household.',
 'input_sentence_2': 'He never found good support in family, and turned to gangs.',
 'input_sentence_3': "It wasn't long before Rick got shot in a robbery.",
 'input_sentence_4': 'The incident caused him to turn a new leaf.',
 'sentence_quiz1': 'He is happy now.',
 'sentence_quiz2': 'He joined a gang.',
 'story_id': '138d5bfb-05cc-41e3-bf2c-fa85ebad14e2'}
Data Fields
The data fields are the same among all splits.
input_sentence_1: The first statement in the story.input_sentence_2: The second statement in the story.input_sentence_3: The third statement in the story.input_sentence_4: The forth statement in the story.sentence_quiz1: first possible continuation of the story.sentence_quiz2: second possible continuation of the story.answer_right_ending: correct possible ending; either 1 or 2.story_id: story id.
Data Splits
| name | validation | test | 
|---|---|---|
| 2016 | 1871 | 1871 | 
| 2018 | 1571 | - | 
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
Citation Information
@inproceedings{mostafazadeh2017lsdsem,
  title={Lsdsem 2017 shared task: The story cloze test},
  author={Mostafazadeh, Nasrin and Roth, Michael and Louis, Annie and Chambers, Nathanael and Allen, James},
  booktitle={Proceedings of the 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics},
  pages={46--51},
  year={2017}
}
Contributions
Thanks to @zaidalyafeai.
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Homepage:
		
			cs.rochester.edu
Paper:
		
			Lsdsem 2017 shared task: The story cloze test
Point of Contact:
		
			Nasrin Mostafazadeh
Size of downloaded dataset files:
		
			2.13 MB
Models trained or fine-tuned on LSDSem/story_cloze
			Text Classification
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				0.2B
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