tasksource/deberta-small-long-nli
Zero-Shot Classification
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Datasets:
Tasks:
Multiple Choice
Sub-tasks:
multiple-choice-qa
Languages:
English
Size:
10K<n<100K
ArXiv:
License:
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Dataset Card for "cosmos_qa"
Dataset Summary
Cosmos QA is a large-scale dataset of 35.6K problems that require commonsense-based reading comprehension, formulated as multiple-choice questions. It focuses on reading between the lines over a diverse collection of people's everyday narratives, asking questions concerning on the likely causes or effects of events that require reasoning beyond the exact text spans in the context
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
default
- Size of downloaded dataset files: 24.40 MB
- Size of the generated dataset: 24.51 MB
- Total amount of disk used: 48.91 MB
An example of 'validation' looks as follows.
This example was too long and was cropped:
{
"answer0": "If he gets married in the church he wo nt have to get a divorce .",
"answer1": "He wants to get married to a different person .",
"answer2": "He wants to know if he does nt like this girl can he divorce her ?",
"answer3": "None of the above choices .",
"context": "\"Do i need to go for a legal divorce ? I wanted to marry a woman but she is not in the same religion , so i am not concern of th...",
"id": "3BFF0DJK8XA7YNK4QYIGCOG1A95STE##3180JW2OT5AF02OISBX66RFOCTG5J7##A2LTOS0AZ3B28A##Blog_56156##q1_a1##378G7J1SJNCDAAIN46FM2P7T6KZEW2",
"label": 1,
"question": "Why is this person asking about divorce ?"
}
Data Fields
The data fields are the same among all splits.
default
id: astringfeature.context: astringfeature.question: astringfeature.answer0: astringfeature.answer1: astringfeature.answer2: astringfeature.answer3: astringfeature.label: aint32feature.
Data Splits
| name | train | validation | test |
|---|---|---|---|
| default | 25262 | 2985 | 6963 |
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
As reported via email by Yejin Choi, the dataset is licensed under CC BY 4.0 license.
Citation Information
@inproceedings{huang-etal-2019-cosmos,
title = "Cosmos {QA}: Machine Reading Comprehension with Contextual Commonsense Reasoning",
author = "Huang, Lifu and
Le Bras, Ronan and
Bhagavatula, Chandra and
Choi, Yejin",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/D19-1243",
doi = "10.18653/v1/D19-1243",
pages = "2391--2401",
}
Contributions
Thanks to @patrickvonplaten, @lewtun, @albertvillanova, @thomwolf for adding this dataset.
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Homepage:
wilburone.github.io
Repository:
github.com
Paper:
Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning
Point of Contact:
Lifu Huang
Size of downloaded dataset files:
24.40 MB
