
# Dataset Card for "hotpot_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://hotpotqa.github.io/](https://hotpotqa.github.io/)
- **Repository:** https://github.com/hotpotqa/hotpot
- **Paper:** [HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering](https://arxiv.org/abs/1809.09600)
- **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:** 1.27 GB
- **Size of the generated dataset:** 1.24 GB
- **Total amount of disk used:** 2.52 GB

### Dataset Summary

HotpotQA is a new dataset with 113k  Wikipedia-based question-answer  pairs with  four  key  features:  (1)  the  questions  require finding and reasoning over multiple supporting  documents  to  answer;  (2)  the  questions  are  diverse  and  not  constrained  to  any pre-existing  knowledge  bases  or  knowledge schemas;  (3)  we  provide  sentence-level  supporting facts required for reasoning, allowingQA systems to reason with strong supervision and explain the predictions; (4) we offer a new type  of  factoid  comparison  questions  to  test QA  systems’  ability  to  extract  relevant  facts and perform necessary comparison.

### 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

#### distractor

- **Size of downloaded dataset files:** 612.75 MB
- **Size of the generated dataset:** 598.66 MB
- **Total amount of disk used:** 1.21 GB

An example of 'validation' looks as follows.
```
{
    "answer": "This is the answer",
    "context": {
        "sentences": [["Sent 1"], ["Sent 21", "Sent 22"]],
        "title": ["Title1", "Title 2"]
    },
    "id": "000001",
    "level": "medium",
    "question": "What is the answer?",
    "supporting_facts": {
        "sent_id": [0, 1, 3],
        "title": ["Title of para 1", "Title of para 2", "Title of para 3"]
    },
    "type": "comparison"
}
```

#### fullwiki

- **Size of downloaded dataset files:** 660.10 MB
- **Size of the generated dataset:** 645.80 MB
- **Total amount of disk used:** 1.31 GB

An example of 'train' looks as follows.
```
{
    "answer": "This is the answer",
    "context": {
        "sentences": [["Sent 1"], ["Sent 2"]],
        "title": ["Title1", "Title 2"]
    },
    "id": "000001",
    "level": "hard",
    "question": "What is the answer?",
    "supporting_facts": {
        "sent_id": [0, 1, 3],
        "title": ["Title of para 1", "Title of para 2", "Title of para 3"]
    },
    "type": "bridge"
}
```

### Data Fields

The data fields are the same among all splits.

#### distractor
- `id`: a `string` feature.
- `question`: a `string` feature.
- `answer`: a `string` feature.
- `type`: a `string` feature.
- `level`: a `string` feature.
- `supporting_facts`: a dictionary feature containing:
  - `title`: a `string` feature.
  - `sent_id`: a `int32` feature.
- `context`: a dictionary feature containing:
  - `title`: a `string` feature.
  - `sentences`: a `list` of `string` features.

#### fullwiki
- `id`: a `string` feature.
- `question`: a `string` feature.
- `answer`: a `string` feature.
- `type`: a `string` feature.
- `level`: a `string` feature.
- `supporting_facts`: a dictionary feature containing:
  - `title`: a `string` feature.
  - `sent_id`: a `int32` feature.
- `context`: a dictionary feature containing:
  - `title`: a `string` feature.
  - `sentences`: a `list` of `string` features.

### Data Splits

#### distractor

|          |train|validation|
|----------|----:|---------:|
|distractor|90447|      7405|

#### fullwiki

|        |train|validation|test|
|--------|----:|---------:|---:|
|fullwiki|90447|      7405|7405|

## 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

HotpotQA is distributed under a [CC BY-SA 4.0 License](http://creativecommons.org/licenses/by-sa/4.0/).

### Citation Information

```
@inproceedings{yang2018hotpotqa,
  title={{HotpotQA}: A Dataset for Diverse, Explainable Multi-hop Question Answering},
  author={Yang, Zhilin and Qi, Peng and Zhang, Saizheng and Bengio, Yoshua and Cohen, William W. and Salakhutdinov, Ruslan and Manning, Christopher D.},
  booktitle={Conference on Empirical Methods in Natural Language Processing ({EMNLP})},
  year={2018}
}
```

### Contributions

Thanks to [@albertvillanova](https://github.com/albertvillanova), [@ghomasHudson](https://github.com/ghomasHudson) for adding this dataset.
task_categories:question-answering annotations_creators:crowdsourced language_creators:found multilinguality:monolingual size_categories:100K<n<1M source_datasets:original language:en license:cc-by-sa-4.0 multi-hop arxiv:1809.09600 region:us
{"annotations_creators": ["crowdsourced"], "language_creators": ["found"], "language": ["en"], "license": ["cc-by-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["original"], "task_categories": ["question-answering"], "task_ids": [], "paperswithcode_id": "hotpotqa", "pretty_name": "HotpotQA", "tags": ["multi-hop"], "dataset_info": [{"config_name": "distractor", "features": [{"name": "id", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "level", "dtype": "string"}, {"name": "supporting_facts", "sequence": [{"name": "title", "dtype": "string"}, {"name": "sent_id", "dtype": "int32"}]}, {"name": "context", "sequence": [{"name": "title", "dtype": "string"}, {"name": "sentences", "sequence": "string"}]}], "splits": [{"name": "train", "num_bytes": 552949315, "num_examples": 90447}, {"name": "validation", "num_bytes": 45716111, "num_examples": 7405}], "download_size": 612746344, "dataset_size": 598665426}, {"config_name": "fullwiki", "features": [{"name": "id", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}, {"name": "type", "dtype": "string"}, {"name": "level", "dtype": "string"}, {"name": "supporting_facts", "sequence": [{"name": "title", "dtype": "string"}, {"name": "sent_id", "dtype": "int32"}]}, {"name": "context", "sequence": [{"name": "title", "dtype": "string"}, {"name": "sentences", "sequence": "string"}]}], "splits": [{"name": "train", "num_bytes": 552949315, "num_examples": 90447}, {"name": "validation", "num_bytes": 46848601, "num_examples": 7405}, {"name": "test", "num_bytes": 46000102, "num_examples": 7405}], "download_size": 660094672, "dataset_size": 645798018}]}
TAGS
#task_categories-question-answering #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #language-English #license-cc-by-sa-4.0 #multi-hop #arxiv-1809.09600 #region-us 

Dataset Card for "hotpot\_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: HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
* Point of Contact:
* Size of downloaded dataset files: 1.27 GB
* Size of the generated dataset: 1.24 GB
* Total amount of disk used: 2.52 GB


### Dataset Summary


HotpotQA is a new dataset with 113k Wikipedia-based question-answer pairs with four key features: (1) the questions require finding and reasoning over multiple supporting documents to answer; (2) the questions are diverse and not constrained to any pre-existing knowledge bases or knowledge schemas; (3) we provide sentence-level supporting facts required for reasoning, allowingQA systems to reason with strong supervision and explain the predictions; (4) we offer a new type of factoid comparison questions to test QA systems’ ability to extract relevant facts and perform necessary comparison.


### Supported Tasks and Leaderboards


### Languages


Dataset Structure
-----------------


### Data Instances


#### distractor


* Size of downloaded dataset files: 612.75 MB
* Size of the generated dataset: 598.66 MB
* Total amount of disk used: 1.21 GB


An example of 'validation' looks as follows.


#### fullwiki


* Size of downloaded dataset files: 660.10 MB
* Size of the generated dataset: 645.80 MB
* Total amount of disk used: 1.31 GB


An example of 'train' looks as follows.


### Data Fields


The data fields are the same among all splits.


#### distractor


* 'id': a 'string' feature.
* 'question': a 'string' feature.
* 'answer': a 'string' feature.
* 'type': a 'string' feature.
* 'level': a 'string' feature.
* 'supporting\_facts': a dictionary feature containing:
	+ 'title': a 'string' feature.
	+ 'sent\_id': a 'int32' feature.
* 'context': a dictionary feature containing:
	+ 'title': a 'string' feature.
	+ 'sentences': a 'list' of 'string' features.


#### fullwiki


* 'id': a 'string' feature.
* 'question': a 'string' feature.
* 'answer': a 'string' feature.
* 'type': a 'string' feature.
* 'level': a 'string' feature.
* 'supporting\_facts': a dictionary feature containing:
	+ 'title': a 'string' feature.
	+ 'sent\_id': a 'int32' feature.
* 'context': a dictionary feature containing:
	+ 'title': a 'string' feature.
	+ 'sentences': a 'list' of 'string' features.


### Data Splits


#### distractor



#### fullwiki



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


HotpotQA is distributed under a CC BY-SA 4.0 License.


### Contributions


Thanks to @albertvillanova, @ghomasHudson for adding this dataset.



### Dataset Summary


HotpotQA is a new dataset with 113k Wikipedia-based question-answer pairs with four key features: (1) the questions require finding and reasoning over multiple supporting documents to answer; (2) the questions are diverse and not constrained to any pre-existing knowledge bases or knowledge schemas; (3) we provide sentence-level supporting facts required for reasoning, allowingQA systems to reason with strong supervision and explain the predictions; (4) we offer a new type of factoid comparison questions to test QA systems’ ability to extract relevant facts and perform necessary comparison. ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### distractor


* Size of downloaded dataset files: 612.75 MB
* Size of the generated dataset: 598.66 MB
* Total amount of disk used: 1.21 GB


An example of 'validation' looks as follows. #### fullwiki


* Size of downloaded dataset files: 660.10 MB
* Size of the generated dataset: 645.80 MB
* Total amount of disk used: 1.31 GB


An example of 'train' looks as follows. ### Data Fields


The data fields are the same among all splits. #### distractor


* 'id': a 'string' feature.
* 'question': a 'string' feature.
* 'answer': a 'string' feature.
* 'type': a 'string' feature.
* 'level': a 'string' feature.
* 'supporting\_facts': a dictionary feature containing:
	+ 'title': a 'string' feature.
	+ 'sent\_id': a 'int32' feature.
* 'context': a dictionary feature containing:
	+ 'title': a 'string' feature.
	+ 'sentences': a 'list' of 'string' features. #### fullwiki


* 'id': a 'string' feature.
* 'question': a 'string' feature.
* 'answer': a 'string' feature.
* 'type': a 'string' feature.
* 'level': a 'string' feature.
* 'supporting\_facts': a dictionary feature containing:
	+ 'title': a 'string' feature.
	+ 'sent\_id': a 'int32' feature.
* 'context': a dictionary feature containing:
	+ 'title': a 'string' feature.
	+ 'sentences': a 'list' of 'string' features. ### Data Splits #### distractor #### fullwiki



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


HotpotQA is distributed under a CC BY-SA 4.0 License. ### Contributions


Thanks to @albertvillanova, @ghomasHudson for adding this dataset.
TAGS
#task_categories-question-answering #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #language-English #license-cc-by-sa-4.0 #multi-hop #arxiv-1809.09600 #region-us 
 ### Dataset Summary


HotpotQA is a new dataset with 113k Wikipedia-based question-answer pairs with four key features: (1) the questions require finding and reasoning over multiple supporting documents to answer; (2) the questions are diverse and not constrained to any pre-existing knowledge bases or knowledge schemas; (3) we provide sentence-level supporting facts required for reasoning, allowingQA systems to reason with strong supervision and explain the predictions; (4) we offer a new type of factoid comparison questions to test QA systems’ ability to extract relevant facts and perform necessary comparison. ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### distractor


* Size of downloaded dataset files: 612.75 MB
* Size of the generated dataset: 598.66 MB
* Total amount of disk used: 1.21 GB


An example of 'validation' looks as follows. #### fullwiki


* Size of downloaded dataset files: 660.10 MB
* Size of the generated dataset: 645.80 MB
* Total amount of disk used: 1.31 GB


An example of 'train' looks as follows. ### Data Fields


The data fields are the same among all splits. #### distractor


* 'id': a 'string' feature.
* 'question': a 'string' feature.
* 'answer': a 'string' feature.
* 'type': a 'string' feature.
* 'level': a 'string' feature.
* 'supporting\_facts': a dictionary feature containing:
	+ 'title': a 'string' feature.
	+ 'sent\_id': a 'int32' feature.
* 'context': a dictionary feature containing:
	+ 'title': a 'string' feature.
	+ 'sentences': a 'list' of 'string' features. #### fullwiki


* 'id': a 'string' feature.
* 'question': a 'string' feature.
* 'answer': a 'string' feature.
* 'type': a 'string' feature.
* 'level': a 'string' feature.
* 'supporting\_facts': a dictionary feature containing:
	+ 'title': a 'string' feature.
	+ 'sent\_id': a 'int32' feature.
* 'context': a dictionary feature containing:
	+ 'title': a 'string' feature.
	+ 'sentences': a 'list' of 'string' features. ### Data Splits #### distractor #### fullwiki



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


HotpotQA is distributed under a CC BY-SA 4.0 License. ### Contributions


Thanks to @albertvillanova, @ghomasHudson for adding this dataset.
passage: TAGS
#task_categories-question-answering #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #language-English #license-cc-by-sa-4.0 #multi-hop #arxiv-1809.09600 #region-us 
### Dataset Summary


HotpotQA is a new dataset with 113k Wikipedia-based question-answer pairs with four key features: (1) the questions require finding and reasoning over multiple supporting documents to answer; (2) the questions are diverse and not constrained to any pre-existing knowledge bases or knowledge schemas; (3) we provide sentence-level supporting facts required for reasoning, allowingQA systems to reason with strong supervision and explain the predictions; (4) we offer a new type of factoid comparison questions to test QA systems’ ability to extract relevant facts and perform necessary comparison.### Supported Tasks and Leaderboards### Languages


Dataset Structure
-----------------### Data Instances#### distractor


* Size of downloaded dataset files: 612.75 MB
* Size of the generated dataset: 598.66 MB
* Total amount of disk used: 1.21 GB


An example of 'validation' looks as follows.#### fullwiki


* Size of downloaded dataset files: 660.10 MB
* Size of the generated dataset: 645.80 MB
* Total amount of disk used: 1.31 GB


An example of 'train' looks as follows.### Data Fields


The data fields are the same among all splits.