commonsense_qa

# Dataset Card for "commonsense_qa"

## Table of Contents
- [Table of Contents](#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://www.tau-nlp.org/commonsenseqa
- **Repository:** https://github.com/jonathanherzig/commonsenseqa
- **Paper:** https://arxiv.org/abs/1811.00937
- **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:** 4.68 MB
- **Size of the generated dataset:** 2.18 MB
- **Total amount of disk used:** 6.86 MB

### Dataset Summary

CommonsenseQA is a new multiple-choice question answering dataset that requires different types of commonsense knowledge
to predict the correct answers . It contains 12,102 questions with one correct answer and four distractor answers.
The dataset is provided in two major training/validation/testing set splits: "Random split" which is the main evaluation
split, and "Question token split", see paper for details.

### Supported Tasks and Leaderboards

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

### Languages

The dataset is in English (`en`).

## Dataset Structure

### Data Instances

#### default

- **Size of downloaded dataset files:** 4.68 MB
- **Size of the generated dataset:** 2.18 MB
- **Total amount of disk used:** 6.86 MB

An example of 'train' looks as follows:
```
{'id': '075e483d21c29a511267ef62bedc0461',
'question': 'The sanctions against the school were a punishing blow, and they seemed to what the efforts the school had made to change?',
'question_concept': 'punishing',
'choices': {'label': ['A', 'B', 'C', 'D', 'E'],
'text': ['ignore', 'enforce', 'authoritarian', 'yell at', 'avoid']},
'answerKey': 'A'}
```

### Data Fields

The data fields are the same among all splits.

#### default
- `id` (`str`): Unique ID.
- `question`: a `string` feature.
- `question_concept` (`str`): ConceptNet concept associated to the question.
- `choices`: a dictionary feature containing:
- `label`: a `string` feature.
- `text`: a `string` feature.
- `answerKey`: a `string` feature.

### Data Splits

| name | train | validation | test |
|---------|------:|-----------:|-----:|
| default | 9741 | 1221 | 1140 |

## 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

The dataset is licensed under the MIT License.

See: https://github.com/jonathanherzig/commonsenseqa/issues/5

### Citation Information

```
@inproceedings{talmor-etal-2019-commonsenseqa,
title = "{C}ommonsense{QA}: A Question Answering Challenge Targeting Commonsense Knowledge",
author = "Talmor, Alon and
Herzig, Jonathan and
Lourie, Nicholas and
Berant, Jonathan",
booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N19-1421",
doi = "10.18653/v1/N19-1421",
pages = "4149--4158",
archivePrefix = "arXiv",
eprint = "1811.00937",
primaryClass = "cs",
}
```

### Contributions

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

# 数据集卡片："commonsense_qa"

## 目录
- [目录](#table-of-contents)
- [数据集描述](#dataset-description)
- [数据集概述](#dataset-summary)
- [支持任务与排行榜](#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](#annotations)
- [个人与敏感信息](#personal-and-sensitive-information)
- [数据集使用注意事项](#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)
- [数据集管理者](#dataset-curators)
- [许可信息](#licensing-information)
- [引用信息](#citation-information)
- [贡献者](#contributions)

## 数据集描述
- **主页链接**：https://www.tau-nlp.org/commonsenseqa
- **代码仓库**：https://github.com/jonathanherzig/commonsenseqa
- **相关论文**：https://arxiv.org/abs/1811.00937
- **联系方式**：[需补充更多信息](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **下载数据集文件大小**：4.68 MB
- **生成后数据集大小**：2.18 MB
- **总磁盘占用空间**：6.86 MB

### 数据集概述
CommonsenseQA是一款全新的多项选择题问答数据集，需依托多类常识知识方可预测正确答案。该数据集包含12102道题目，每道题目配有1个正确答案与4个干扰项答案。本数据集采用两种主流的训练/验证/测试集划分方式：作为主要评估划分的“随机划分”，以及“问题Token（Token）划分”，详细说明请参阅相关论文。

### 支持任务与排行榜
[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
本数据集采用英文（`en`）编写。

## 数据集结构

### 数据实例

#### 默认模式
- **下载数据集文件大小**：4.68 MB
- **生成后数据集大小**：2.18 MB
- **总磁盘占用空间**：6.86 MB

以下是一个「训练集」样本示例：

{'id': '075e483d21c29a511267ef62bedc0461',
'question': 'The sanctions against the school were a punishing blow, and they seemed to what the efforts the school had made to change?',
'question_concept': 'punishing',
'choices': {'label': ['A', 'B', 'C', 'D', 'E'],
'text': ['ignore', 'enforce', 'authoritarian', 'yell at', 'avoid']},
'answerKey': 'A'}

### 数据字段
所有数据集划分的数据字段格式保持一致。

#### 默认模式
- `id`（字符串类型）：唯一标识符。
- `question`：字符串类型特征。
- `question_concept`（字符串类型）：与该问题关联的概念网（ConceptNet）概念。
- `choices`：字典类型特征，包含以下子字段：
- `label`：字符串类型特征。
- `text`：字符串类型特征。
- `answerKey`（字符串类型）：正确答案的键值。

### 数据划分

| 划分名称 | 训练集 | 验证集 | 测试集 |
|---------|------:|-----------:|-----:|
| 默认模式 | 9741 | 1221 | 1140 |

## 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

#### 初始数据收集与标准化
[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

#### 标注流程
[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)

## 数据集使用注意事项

### 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

### 数据集管理者
[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
本数据集采用MIT许可证进行授权。

参阅：https://github.com/jonathanherzig/commonsenseqa/issues/5

### 引用信息

@inproceedings{talmor-etal-2019-commonsenseqa,
title = "{C}ommonsense{QA}: A Question Answering Challenge Targeting Commonsense Knowledge",
author = "Talmor, Alon and
Herzig, Jonathan and
Lourie, Nicholas and
Berant, Jonathan",
booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N19-1421",
doi = "10.18653/v1/N19-1421",
pages = "4149--4158",
archivePrefix = "arXiv",
eprint = "1811.00937",
primaryClass = "cs",
}

### 贡献者
感谢 [@thomwolf](https://github.com/thomwolf)、[@lewtun](https://github.com/lewtun)、[@albertvillanova](https://github.com/albertvillanova)、[@patrickvonplaten](https://github.com/patrickvonplaten) 为本数据集的收录提供的贡献。