
# 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.
task_categories:question-answering task_categories:text2text-generation task_ids:open-domain-qa task_ids:open-domain-abstractive-qa task_ids:extractive-qa task_ids:abstractive-qa annotations_creators:crowdsourced language_creators:machine-generated multilinguality:monolingual size_categories:10K<n<100K size_categories:100K<n<1M source_datasets:original language:en license:unknown arxiv:1705.03551 region:us
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"normalized_matched_wiki_entity_name", "dtype": "string"}, {"name": "normalized_value", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "value", "dtype": "string"}]}], "splits": [{"name": "train"}, {"name": "validation"}, {"name": "test"}], "download_size": 3298328560, "dataset_size": 0}, {"config_name": "unfiltered.web.nocontext", "features": [{"name": "question", "dtype": "string"}, {"name": "question_id", "dtype": "string"}, {"name": "question_source", "dtype": "string"}, {"name": "entity_pages", "sequence": [{"name": "doc_source", "dtype": "string"}, {"name": "filename", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "wiki_context", "dtype": "string"}]}, {"name": "search_results", "sequence": [{"name": "description", "dtype": "string"}, {"name": "filename", "dtype": "string"}, {"name": "rank", "dtype": "int32"}, {"name": "title", "dtype": "string"}, {"name": "url", "dtype": "string"}, {"name": "search_context", "dtype": "string"}]}, {"name": "answer", "struct": [{"name": "aliases", "sequence": "string"}, {"name": "normalized_aliases", "sequence": "string"}, {"name": "matched_wiki_entity_name", "dtype": "string"}, {"name": "normalized_matched_wiki_entity_name", "dtype": "string"}, {"name": "normalized_value", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "value", "dtype": "string"}]}], "splits": [{"name": "train"}, {"name": "validation"}, {"name": "test"}], "download_size": 632549060, "dataset_size": 0}, {"config_name": "unfiltered.wikipedia", "features": [{"name": "question", "dtype": "string"}, {"name": "question_id", "dtype": "string"}, {"name": "question_source", "dtype": "string"}, {"name": "entity_pages", "sequence": [{"name": "doc_source", "dtype": "string"}, {"name": "filename", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "wiki_context", "dtype": "string"}]}, {"name": "search_results", "sequence": [{"name": "description", "dtype": "string"}, {"name": "filename", "dtype": "string"}, {"name": "rank", "dtype": "int32"}, {"name": "title", "dtype": "string"}, {"name": "url", "dtype": "string"}, {"name": "search_context", "dtype": "string"}]}, {"name": "answer", "struct": [{"name": "aliases", "sequence": "string"}, {"name": "normalized_aliases", "sequence": "string"}, {"name": "matched_wiki_entity_name", "dtype": "string"}, {"name": "normalized_matched_wiki_entity_name", "dtype": "string"}, {"name": "normalized_value", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "value", "dtype": "string"}]}], "splits": [{"name": "train"}, {"name": "validation"}, {"name": "test"}], "download_size": 3298328560, "dataset_size": 0}, {"config_name": "unfiltered.wikipedia.nocontext", "features": [{"name": "question", "dtype": "string"}, {"name": "question_id", "dtype": "string"}, {"name": "question_source", "dtype": "string"}, {"name": "entity_pages", "sequence": [{"name": "doc_source", "dtype": "string"}, {"name": "filename", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "wiki_context", "dtype": "string"}]}, {"name": "search_results", "sequence": [{"name": "description", "dtype": "string"}, {"name": "filename", "dtype": "string"}, {"name": "rank", "dtype": "int32"}, {"name": "title", "dtype": "string"}, {"name": "url", "dtype": "string"}, {"name": "search_context", "dtype": "string"}]}, {"name": "answer", "struct": [{"name": "aliases", "sequence": "string"}, {"name": "normalized_aliases", "sequence": "string"}, {"name": "matched_wiki_entity_name", "dtype": "string"}, {"name": "normalized_matched_wiki_entity_name", "dtype": "string"}, {"name": "normalized_value", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "value", "dtype": "string"}]}], "splits": [{"name": "train"}, {"name": "validation"}, {"name": "test"}], "download_size": 632549060, "dataset_size": 0}], "configs": [{"config_name": "rc", "data_files": [{"split": "train", "path": "rc/train-*"}, {"split": "validation", "path": "rc/validation-*"}, {"split": "test", "path": "rc/test-*"}]}, {"config_name": "rc.nocontext", "data_files": [{"split": "train", "path": "rc.nocontext/train-*"}, {"split": "validation", "path": "rc.nocontext/validation-*"}, {"split": "test", "path": "rc.nocontext/test-*"}]}, {"config_name": "rc.web", "data_files": [{"split": "train", "path": "rc.web/train-*"}, {"split": "validation", "path": "rc.web/validation-*"}, {"split": "test", "path": "rc.web/test-*"}]}, {"config_name": "rc.web.nocontext", "data_files": [{"split": "train", "path": "rc.web.nocontext/train-*"}, {"split": "validation", "path": "rc.web.nocontext/validation-*"}, {"split": "test", "path": "rc.web.nocontext/test-*"}]}, {"config_name": "rc.wikipedia", "data_files": [{"split": "train", "path": "rc.wikipedia/train-*"}, {"split": "validation", "path": "rc.wikipedia/validation-*"}, {"split": "test", "path": "rc.wikipedia/test-*"}]}, {"config_name": "rc.wikipedia.nocontext", "data_files": [{"split": "train", "path": "rc.wikipedia.nocontext/train-*"}, {"split": "validation", "path": "rc.wikipedia.nocontext/validation-*"}, {"split": "test", "path": "rc.wikipedia.nocontext/test-*"}]}, {"config_name": "unfiltered", "data_files": [{"split": "train", "path": "unfiltered/train-*"}, {"split": "validation", "path": "unfiltered/validation-*"}, {"split": "test", "path": "unfiltered/test-*"}]}, {"config_name": "unfiltered.nocontext", "data_files": [{"split": "train", "path": "unfiltered.nocontext/train-*"}, {"split": "validation", "path": "unfiltered.nocontext/validation-*"}, {"split": "test", "path": "unfiltered.nocontext/test-*"}]}]}
TAGS
#task_categories-question-answering #task_categories-text2text-generation #task_ids-open-domain-qa #task_ids-open-domain-abstractive-qa #task_ids-extractive-qa #task_ids-abstractive-qa #annotations_creators-crowdsourced #language_creators-machine-generated #multilinguality-monolingual #size_categories-10K<n<100K #size_categories-100K<n<1M #source_datasets-original #language-English #license-unknown #arxiv-1705.03551 #region-us 

Dataset Card for "trivia\_qa"
=============================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks and Leaderboards
	+ Languages
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splits
* Dataset Creation
	+ Curation Rationale
	+ Source Data
	+ Annotations
	+ 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
	+ Citation Information
	+ Contributions


Dataset Description
-------------------


* Homepage: URL
* Repository: URL
* Paper: TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension
* Leaderboard: CodaLab Leaderboard
* Point of Contact:
* 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


### 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



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


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


### Contributions


Thanks to @thomwolf, @patrickvonplaten, @lewtun for adding this dataset.



### 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 ### 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



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


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


Thanks to @thomwolf, @patrickvonplaten, @lewtun for adding this dataset.
TAGS
#task_categories-question-answering #task_categories-text2text-generation #task_ids-open-domain-qa #task_ids-open-domain-abstractive-qa #task_ids-extractive-qa #task_ids-abstractive-qa #annotations_creators-crowdsourced #language_creators-machine-generated #multilinguality-monolingual #size_categories-10K<n<100K #size_categories-100K<n<1M #source_datasets-original #language-English #license-unknown #arxiv-1705.03551 #region-us 
 ### 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 ### 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



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


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


Thanks to @thomwolf, @patrickvonplaten, @lewtun for adding this dataset.