cosmos_qa

# Dataset Card for "cosmos_qa"

## 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:** [https://wilburone.github.io/cosmos/](https://wilburone.github.io/cosmos/)
- **Repository:** https://github.com/wilburOne/cosmosqa/
- **Paper:** [Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning](https://arxiv.org/abs/1909.00277)
- **Point of Contact:** [Lifu Huang](mailto:[e-mail])
- **Size of downloaded dataset files:** 24.40 MB
- **Size of the generated dataset:** 24.51 MB
- **Total amount of disk used:** 48.91 MB

### 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

[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

#### 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`: a `string` feature.
- `context`: a `string` feature.
- `question`: a `string` feature.
- `answer0`: a `string` feature.
- `answer1`: a `string` feature.
- `answer2`: a `string` feature.
- `answer3`: a `string` feature.
- `label`: a `int32` feature.

### Data Splits

| name |train|validation|test|
|-------|----:|---------:|---:|
|default|25262| 2985|6963|

## 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

As reported via email by Yejin Choi, the dataset is licensed under [CC BY 4.0](https://creativecommons.org/licenses/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](https://github.com/patrickvonplaten), [@lewtun](https://github.com/lewtun), [@albertvillanova](https://github.com/albertvillanova), [@thomwolf](https://github.com/thomwolf) for adding this dataset.

# 「cosmos_qa」数据集卡片

## 目录
- [数据集描述](#dataset-description)
- [数据集概况](#dataset-summary)
- [支持任务与基准榜单](#supported-tasks-and-leaderboards)
- [语言](#languages)
- [数据集结构](#dataset-structure)
- [数据实例](#data-instances)
- [数据字段](#data-fields)
- [数据划分](#data-splits)
- [数据集构建](#dataset-creation)
- [构建初衷](#curation-rationale)
- [源数据](#source-data)
- [标注流程](#annotations)
- [个人与敏感信息](#personal-and-sensitive-information)
- [数据使用注意事项](#considerations-for-using-the-data)
- [数据集的社会影响](#social-impact-of-dataset)
- [偏差讨论](#discussion-of-biases)
- [其他已知局限性](#other-known-limitations)
- [附加信息](#additional-information)
- [数据集维护者](#dataset-curators)
- [许可信息](#licensing-information)
- [引用信息](#citation-information)
- [贡献者](#contributions)

## 数据集描述
- **主页:** [https://wilburone.github.io/cosmos/](https://wilburone.github.io/cosmos/)
- **代码仓库:** https://github.com/wilburOne/cosmosqa/
- **相关论文:** [Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning](https://arxiv.org/abs/1909.00277)
- **联系人:** [Lifu Huang](mailto:[e-mail])
- **下载数据集文件大小:** 24.40 MB
- **生成后数据集大小:** 24.51 MB
- **总磁盘占用:** 48.91 MB

### 数据集概况
Cosmos QA是一个包含35.6K个需基于常识的阅读理解问题的大规模数据集，采用多项选择题形式。该数据集聚焦于从多样化的大众日常叙事文本中挖掘言外之意，提出的问题涉及事件的潜在成因或影响，需要超越上下文精确文本片段的推理能力。

### 支持任务与基准榜单
[需补充更多信息](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### 语言
[需补充更多信息](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## 数据集结构
### 数据实例
#### 默认配置
- **下载数据集文件大小:** 24.40 MB
- **生成后数据集大小:** 24.51 MB
- **总磁盘占用:** 48.91 MB

以下是「验证集」的一个示例：

该示例过长已被截断：

{
"answer0": "如果他在教堂结婚，就不必离婚。",
"answer1": "他想和另一个人结婚。",
"answer2": "他想知道如果他不喜欢这个女孩，能不能和她离婚？",
"answer3": "以上选项均不符合",
"context": ""我需要办理合法离婚吗？我想娶一位女性，但她的宗教信仰与我不同，所以我不担心……"",
"id": "3BFF0DJK8XA7YNK4QYIGCOG1A95STE##3180JW2OT5AF02OISBX66RFOCTG5J7##A2LTOS0AZ3B28A##Blog_56156##q1_a1##378G7J1SJNCDAAIN46FM2P7T6KZEW2",
"label": 1,
"question": "这个人为什么要询问离婚相关的问题？"
}

### 数据字段
所有数据划分的数据字段格式一致。
#### 默认配置
- `id`: 字符串类型特征
- `context`: 字符串类型特征
- `question`: 字符串类型特征
- `answer0`: 字符串类型特征
- `answer1`: 字符串类型特征
- `answer2`: 字符串类型特征
- `answer3`: 字符串类型特征
- `label`: int32 类型特征

### 数据划分
| 配置名称 | 训练集 | 验证集 | 测试集 |
|---------|-------:|-------:|------:|
| default | 25262 | 2985 | 6963 |

## 数据集构建
### 构建初衷
[需补充更多信息](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### 源数据
#### 初始数据收集与规范化
[需补充更多信息](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### 源语言生成者是谁？
[需补充更多信息](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### 标注流程
#### 标注过程
[需补充更多信息](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### 标注人员是谁？
[需补充更多信息](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### 个人与敏感信息
[需补充更多信息](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## 数据使用注意事项
### 数据集的社会影响
[需补充更多信息](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### 偏差讨论
[需补充更多信息](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### 其他已知局限性
[需补充更多信息](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## 附加信息
### 数据集维护者
[需补充更多信息](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### 许可信息
据Yejin Choi通过邮件告知，该数据集采用[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)许可协议。

### 引用信息

@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",
}

### 贡献者
感谢[@patrickvonplaten](https://github.com/patrickvonplaten)、[@lewtun](https://github.com/lewtun)、[@albertvillanova](https://github.com/albertvillanova)、[@thomwolf](https://github.com/thomwolf) 为本数据集的添加工作。