trivia_qa

# Dataset Card for "trivia_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:** [http://nlp.cs.washington.edu/triviaqa/](http://nlp.cs.washington.edu/triviaqa/)
- **Repository:** [https://github.com/mandarjoshi90/triviaqa](https://github.com/mandarjoshi90/triviaqa)
- **Paper:** [TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension](https://arxiv.org/abs/1705.03551)
- **Leaderboard:** [CodaLab Leaderboard](https://competitions.codalab.org/competitions/17208#results)
- **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:** 9.26 GB
- **Size of the generated dataset:** 45.46 GB
- **Total amount of disk used:** 54.72 GB

### Dataset Summary

TriviaqQA is a reading comprehension dataset containing over 650K
question-answer-evidence triples. TriviaqQA includes 95K question-answer
pairs authored by trivia enthusiasts and independently gathered evidence
documents, six per question on average, that provide high quality distant
supervision for answering the questions.

### Supported Tasks and Leaderboards

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

### Languages

English.

## Dataset Structure

### Data Instances

#### rc

- **Size of downloaded dataset files:** 2.67 GB
- **Size of the generated dataset:** 16.02 GB
- **Total amount of disk used:** 18.68 GB

An example of 'train' looks as follows.
```

```

#### rc.nocontext

- **Size of downloaded dataset files:** 2.67 GB
- **Size of the generated dataset:** 126.27 MB
- **Total amount of disk used:** 2.79 GB

An example of 'train' looks as follows.
```

```

#### unfiltered

- **Size of downloaded dataset files:** 3.30 GB
- **Size of the generated dataset:** 29.24 GB
- **Total amount of disk used:** 32.54 GB

An example of 'validation' looks as follows.
```

```

#### unfiltered.nocontext

- **Size of downloaded dataset files:** 632.55 MB
- **Size of the generated dataset:** 74.56 MB
- **Total amount of disk used:** 707.11 MB

An example of 'train' looks as follows.
```

```

### Data Fields

The data fields are the same among all splits.

#### rc
- `question`: a `string` feature.
- `question_id`: a `string` feature.
- `question_source`: a `string` feature.
- `entity_pages`: a dictionary feature containing:
- `doc_source`: a `string` feature.
- `filename`: a `string` feature.
- `title`: a `string` feature.
- `wiki_context`: a `string` feature.
- `search_results`: a dictionary feature containing:
- `description`: a `string` feature.
- `filename`: a `string` feature.
- `rank`: a `int32` feature.
- `title`: a `string` feature.
- `url`: a `string` feature.
- `search_context`: a `string` feature.
- `aliases`: a `list` of `string` features.
- `normalized_aliases`: a `list` of `string` features.
- `matched_wiki_entity_name`: a `string` feature.
- `normalized_matched_wiki_entity_name`: a `string` feature.
- `normalized_value`: a `string` feature.
- `type`: a `string` feature.
- `value`: a `string` feature.

#### rc.nocontext
- `question`: a `string` feature.
- `question_id`: a `string` feature.
- `question_source`: a `string` feature.
- `entity_pages`: a dictionary feature containing:
- `doc_source`: a `string` feature.
- `filename`: a `string` feature.
- `title`: a `string` feature.
- `wiki_context`: a `string` feature.
- `search_results`: a dictionary feature containing:
- `description`: a `string` feature.
- `filename`: a `string` feature.
- `rank`: a `int32` feature.
- `title`: a `string` feature.
- `url`: a `string` feature.
- `search_context`: a `string` feature.
- `aliases`: a `list` of `string` features.
- `normalized_aliases`: a `list` of `string` features.
- `matched_wiki_entity_name`: a `string` feature.
- `normalized_matched_wiki_entity_name`: a `string` feature.
- `normalized_value`: a `string` feature.
- `type`: a `string` feature.
- `value`: a `string` feature.

#### unfiltered
- `question`: a `string` feature.
- `question_id`: a `string` feature.
- `question_source`: a `string` feature.
- `entity_pages`: a dictionary feature containing:
- `doc_source`: a `string` feature.
- `filename`: a `string` feature.
- `title`: a `string` feature.
- `wiki_context`: a `string` feature.
- `search_results`: a dictionary feature containing:
- `description`: a `string` feature.
- `filename`: a `string` feature.
- `rank`: a `int32` feature.
- `title`: a `string` feature.
- `url`: a `string` feature.
- `search_context`: a `string` feature.
- `aliases`: a `list` of `string` features.
- `normalized_aliases`: a `list` of `string` features.
- `matched_wiki_entity_name`: a `string` feature.
- `normalized_matched_wiki_entity_name`: a `string` feature.
- `normalized_value`: a `string` feature.
- `type`: a `string` feature.
- `value`: a `string` feature.

#### unfiltered.nocontext
- `question`: a `string` feature.
- `question_id`: a `string` feature.
- `question_source`: a `string` feature.
- `entity_pages`: a dictionary feature containing:
- `doc_source`: a `string` feature.
- `filename`: a `string` feature.
- `title`: a `string` feature.
- `wiki_context`: a `string` feature.
- `search_results`: a dictionary feature containing:
- `description`: a `string` feature.
- `filename`: a `string` feature.
- `rank`: a `int32` feature.
- `title`: a `string` feature.
- `url`: a `string` feature.
- `search_context`: a `string` feature.
- `aliases`: a `list` of `string` features.
- `normalized_aliases`: a `list` of `string` features.
- `matched_wiki_entity_name`: a `string` feature.
- `normalized_matched_wiki_entity_name`: a `string` feature.
- `normalized_value`: a `string` feature.
- `type`: a `string` feature.
- `value`: a `string` feature.

### Data Splits

| name |train |validation|test |
|--------------------|-----:|---------:|----:|
|rc |138384| 18669|17210|
|rc.nocontext |138384| 18669|17210|
|unfiltered | 87622| 11313|10832|
|unfiltered.nocontext| 87622| 11313|10832|

## 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 University of Washington does not own the copyright of the questions and documents included in TriviaQA.

### Citation Information

```

@article{2017arXivtriviaqa,
author = {{Joshi}, Mandar and {Choi}, Eunsol and {Weld},
Daniel and {Zettlemoyer}, Luke},
title = "{triviaqa: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension}",
journal = {arXiv e-prints},
year = 2017,
eid = {arXiv:1705.03551},
pages = {arXiv:1705.03551},
archivePrefix = {arXiv},
eprint = {1705.03551},
}

```

### Contributions

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

# “TriviaQA” 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)
- [数据拆分](#data-splits)
- [数据集构建](#dataset-creation)
- [构建初衷](#curation-rationale)
- [源数据](#source-data)
- [标注信息](#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)
- [数据集维护者](#dataset-curators)
- [授权信息](#licensing-information)
- [引用信息](#citation-information)
- [贡献者](#contributions)

## 数据集描述

- **主页:** [http://nlp.cs.washington.edu/triviaqa/](http://nlp.cs.washington.edu/triviaqa/)
- **代码仓库:** [https://github.com/mandarjoshi90/triviaqa](https://github.com/mandarjoshi90/triviaqa)
- **相关论文:** [TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension](https://arxiv.org/abs/1705.03551)
- **排行榜:** [CodaLab 排行榜](https://competitions.codalab.org/competitions/17208#results)
- **联系方式:** [更多信息请见](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:** 9.26 GB
- **生成后数据集大小:** 45.46 GB
- **总磁盘占用空间:** 54.72 GB

### 数据集概况

TriviaQA是一个阅读理解数据集，包含超过65万个问题-答案-证据三元组。该数据集包含9.5万个由问答爱好者创作的问答对，以及平均每个问题对应6个独立收集的证据文档，可为问题解答提供高质量的远程监督信号。

### 支持任务与排行榜

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

### 语言

英语。

## 数据集结构

### 数据实例

#### rc
- **下载数据集文件大小:** 2.67 GB
- **生成后数据集大小:** 16.02 GB
- **总磁盘占用空间:** 18.68 GB

训练集示例格式如下：

#### rc.nocontext
- **下载数据集文件大小:** 2.67 GB
- **生成后数据集大小:** 126.27 MB
- **总磁盘占用空间:** 2.79 GB

训练集示例格式如下：

#### unfiltered
- **下载数据集文件大小:** 3.30 GB
- **生成后数据集大小:** 29.24 GB
- **总磁盘占用空间:** 32.54 GB

验证集示例格式如下：

#### unfiltered.nocontext
- **下载数据集文件大小:** 632.55 MB
- **生成后数据集大小:** 74.56 MB
- **总磁盘占用空间:** 707.11 MB

训练集示例格式如下：

### 数据字段

所有数据拆分的数据字段格式均保持一致。

#### rc
- `"question"`: 字符串特征。
- `"question_id"`: 字符串特征。
- `"question_source"`: 字符串特征。
- `"entity_pages"`: 字典特征，包含以下字段：
- `"doc_source"`: 字符串特征。
- `"filename"`: 字符串特征。
- `"title"`: 字符串特征。
- `"wiki_context"`: 字符串特征。
- `"search_results"`: 字典特征，包含以下字段：
- `"description"`: 字符串特征。
- `"filename"`: 字符串特征。
- `"rank"`: int32 类型特征。
- `"title"`: 字符串特征。
- `"url"`: 字符串特征。
- `"search_context"`: 字符串特征。
- `"aliases"`: 字符串列表特征。
- `"normalized_aliases"`: 字符串列表特征。
- `"matched_wiki_entity_name"`: 字符串特征。
- `"normalized_matched_wiki_entity_name"`: 字符串特征。
- `"normalized_value"`: 字符串特征。
- `"type"`: 字符串特征。
- `"value"`: 字符串特征。

#### rc.nocontext
- `"question"`: 字符串特征。
- `"question_id"`: 字符串特征。
- `"question_source"`: 字符串特征。
- `"entity_pages"`: 字典特征，包含以下字段：
- `"doc_source"`: 字符串特征。
- `"filename"`: 字符串特征。
- `"title"`: 字符串特征。
- `"wiki_context"`: 字符串特征。
- `"search_results"`: 字典特征，包含以下字段：
- `"description"`: 字符串特征。
- `"filename"`: 字符串特征。
- `"rank"`: int32 类型特征。
- `"title"`: 字符串特征。
- `"url"`: 字符串特征。
- `"search_context"`: 字符串特征。
- `"aliases"`: 字符串列表特征。
- `"normalized_aliases"`: 字符串列表特征。
- `"matched_wiki_entity_name"`: 字符串特征。
- `"normalized_matched_wiki_entity_name"`: 字符串特征。
- `"normalized_value"`: 字符串特征。
- `"type"`: 字符串特征。
- `"value"`: 字符串特征。

#### unfiltered
- `"question"`: 字符串特征。
- `"question_id"`: 字符串特征。
- `"question_source"`: 字符串特征。
- `"entity_pages"`: 字典特征，包含以下字段：
- `"doc_source"`: 字符串特征。
- `"filename"`: 字符串特征。
- `"title"`: 字符串特征。
- `"wiki_context"`: 字符串特征。
- `"search_results"`: 字典特征，包含以下字段：
- `"description"`: 字符串特征。
- `"filename"`: 字符串特征。
- `"rank"`: int32 类型特征。
- `"title"`: 字符串特征。
- `"url"`: 字符串特征。
- `"search_context"`: 字符串特征。
- `"aliases"`: 字符串列表特征。
- `"normalized_aliases"`: 字符串列表特征。
- `"matched_wiki_entity_name"`: 字符串特征。
- `"normalized_matched_wiki_entity_name"`: 字符串特征。
- `"normalized_value"`: 字符串特征。
- `"type"`: 字符串特征。
- `"value"`: 字符串特征。

#### unfiltered.nocontext
- `"question"`: 字符串特征。
- `"question_id"`: 字符串特征。
- `"question_source"`: 字符串特征。
- `"entity_pages"`: 字典特征，包含以下字段：
- `"doc_source"`: 字符串特征。
- `"filename"`: 字符串特征。
- `"title"`: 字符串特征。
- `"wiki_context"`: 字符串特征。
- `"search_results"`: 字典特征，包含以下字段：
- `"description"`: 字符串特征。
- `"filename"`: 字符串特征。
- `"rank"`: int32 类型特征。
- `"title"`: 字符串特征。
- `"url"`: 字符串特征。
- `"search_context"`: 字符串特征。
- `"aliases"`: 字符串列表特征。
- `"normalized_aliases"`: 字符串列表特征。
- `"matched_wiki_entity_name"`: 字符串特征。
- `"normalized_matched_wiki_entity_name"`: 字符串特征。
- `"normalized_value"`: 字符串特征。
- `"type"`: 字符串特征。
- `"value"`: 字符串特征。

### 数据拆分

| 拆分名称 | 训练集 | 验证集 | 测试集 |
|---------|-------:|-------:|-------:|
| rc | 138384 | 18669 | 17210 |
| rc.nocontext | 138384 | 18669 | 17210 |
| unfiltered | 87622 | 11313 | 10832 |
| unfiltered.nocontext | 87622 | 11313 | 10832 |

## 数据集构建

### 构建初衷

[更多信息请见](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

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

#### 源语言生成者是谁？

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

### 标注信息

#### 标注流程

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

#### 标注人员是谁？

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

### 个人与敏感信息

[更多信息请见](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

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

### 偏差讨论

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

### 其他已知局限性

[更多信息请见](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

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

### 授权信息

华盛顿大学并非本数据集所包含的问题与文档的版权所有者。

### 引用信息

@article{2017arXivtriviaqa,
author = {{Joshi}, Mandar and {Choi}, Eunsol and {Weld},
Daniel and {Zettlemoyer}, Luke},
title = "{triviaqa: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension}",
journal = {arXiv e-prints},
year = 2017,
eid = {arXiv:1705.03551},
pages = {arXiv:1705.03551},
archivePrefix = {arXiv},
eprint = {1705.03551},
}

### 贡献者

感谢[@thomwolf](https://github.com/thomwolf)、[@patrickvonplaten](https://github.com/patrickvonplaten)与[@lewtun](https://github.com/lewtun)为本数据集的收录提供支持。