Datasets:
cos_e

	---
	annotations_creators:
	- crowdsourced
	language_creators:
	- crowdsourced
	language:
	- en
	license:
	- unknown
	multilinguality:
	- monolingual
	size_categories:
	- 10K<n<100K
	source_datasets:
	- extended\|commonsense_qa
	task_categories:
	- question-answering
	task_ids:
	- open-domain-qa
	paperswithcode_id: cos-e
	pretty_name: Commonsense Explanations
	dataset_info:
	- config_name: v1.0
	features:
	- name: id
	dtype: string
	- name: question
	dtype: string
	- name: choices
	sequence: string
	- name: answer
	dtype: string
	- name: abstractive_explanation
	dtype: string
	- name: extractive_explanation
	dtype: string
	splits:
	- name: train
	num_bytes: 2067971
	num_examples: 7610
	- name: validation
	num_bytes: 260669
	num_examples: 950
	download_size: 1588340
	dataset_size: 2328640
	- config_name: v1.11
	features:
	- name: id
	dtype: string
	- name: question
	dtype: string
	- name: choices
	sequence: string
	- name: answer
	dtype: string
	- name: abstractive_explanation
	dtype: string
	- name: extractive_explanation
	dtype: string
	splits:
	- name: train
	num_bytes: 2702777
	num_examples: 9741
	- name: validation
	num_bytes: 329897
	num_examples: 1221
	download_size: 1947552
	dataset_size: 3032674
	configs:
	- config_name: v1.0
	data_files:
	- split: train
	path: v1.0/train-*
	- split: validation
	path: v1.0/validation-*
	- config_name: v1.11
	data_files:
	- split: train
	path: v1.11/train-*
	- split: validation
	path: v1.11/validation-*
	---

	# Dataset Card for "cos_e"

	## Table of Contents
	- [Dataset Description](#dataset-description)
	- [Dataset Summary](#dataset-summary)
	- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
	- [Languages](#languages)
	- [Dataset Structure](#dataset-structure)
	- [Data Instances](#data-instances)
	- [Data Fields](#data-fields)
	- [Data Splits](#data-splits)
	- [Dataset Creation](#dataset-creation)
	- [Curation Rationale](#curation-rationale)
	- [Source Data](#source-data)
	- [Annotations](#annotations)
	- [Personal and Sensitive Information](#personal-and-sensitive-information)
	- [Considerations for Using the Data](#considerations-for-using-the-data)
	- [Social Impact of Dataset](#social-impact-of-dataset)
	- [Discussion of Biases](#discussion-of-biases)
	- [Other Known Limitations](#other-known-limitations)
	- [Additional Information](#additional-information)
	- [Dataset Curators](#dataset-curators)
	- [Licensing Information](#licensing-information)
	- [Citation Information](#citation-information)
	- [Contributions](#contributions)

	## Dataset Description

	- Homepage:
	- Repository: https://github.com/salesforce/cos-e
	- Paper: [Explain Yourself! Leveraging Language Models for Commonsense Reasoning](https://arxiv.org/abs/1906.02361)
	- Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
	- Size of downloaded dataset files: 10.83 MB
	- Size of the generated dataset: 5.39 MB
	- Total amount of disk used: 16.22 MB

	### Dataset Summary

	Common Sense Explanations (CoS-E) allows for training language models to
	automatically generate explanations that can be used during training and
	inference in a novel Commonsense Auto-Generated Explanation (CAGE) framework.

	### Supported Tasks and Leaderboards

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Languages

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	## Dataset Structure

	### Data Instances

	#### v1.0

	- Size of downloaded dataset files: 4.30 MB
	- Size of the generated dataset: 2.34 MB
	- Total amount of disk used: 6.64 MB

	An example of 'train' looks as follows.
	```
	{
	"abstractive_explanation": "this is open-ended",
	"answer": "b",
	"choices": ["a", "b", "c"],
	"extractive_explanation": "this is selected train",
	"id": "42",
	"question": "question goes here."
	}
	```

	#### v1.11

	- Size of downloaded dataset files: 6.53 MB
	- Size of the generated dataset: 3.05 MB
	- Total amount of disk used: 9.58 MB

	An example of 'train' looks as follows.
	```
	{
	"abstractive_explanation": "this is open-ended",
	"answer": "b",
	"choices": ["a", "b", "c"],
	"extractive_explanation": "this is selected train",
	"id": "42",
	"question": "question goes here."
	}
	```

	### Data Fields

	The data fields are the same among all splits.

	#### v1.0
	- `id`: a `string` feature.
	- `question`: a `string` feature.
	- `choices`: a `list` of `string` features.
	- `answer`: a `string` feature.
	- `abstractive_explanation`: a `string` feature.
	- `extractive_explanation`: a `string` feature.

	#### v1.11
	- `id`: a `string` feature.
	- `question`: a `string` feature.
	- `choices`: a `list` of `string` features.
	- `answer`: a `string` feature.
	- `abstractive_explanation`: a `string` feature.
	- `extractive_explanation`: a `string` feature.

	### Data Splits

	\|name \|train\|validation\|
	\|-----\|----:\|---------:\|
	\|v1.0 \| 7610\| 950\|
	\|v1.11\| 9741\| 1221\|

	## Dataset Creation

	### Curation Rationale

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Source Data

	#### Initial Data Collection and Normalization

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	#### Who are the source language producers?

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Annotations

	#### Annotation process

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	#### Who are the annotators?

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Personal and Sensitive Information

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	## Considerations for Using the Data

	### Social Impact of Dataset

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Discussion of Biases

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Other Known Limitations

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	## Additional Information

	### Dataset Curators

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Licensing Information

	Unknown.

	### Citation Information

	```
	@inproceedings{rajani2019explain,
	title = "Explain Yourself! Leveraging Language models for Commonsense Reasoning",
	author = "Rajani, Nazneen Fatema and
	McCann, Bryan and
	Xiong, Caiming and
	Socher, Richard",
	year="2019",
	booktitle = "Proceedings of the 2019 Conference of the Association for Computational Linguistics (ACL2019)",
	url ="https://arxiv.org/abs/1906.02361"
	}
	```


	### Contributions

	Thanks to [@lewtun](https://github.com/lewtun), [@thomwolf](https://github.com/thomwolf), [@mariamabarham](https://github.com/mariamabarham), [@patrickvonplaten](https://github.com/patrickvonplaten), [@albertvillanova](https://github.com/albertvillanova), [@lhoestq](https://github.com/lhoestq) for adding this dataset.