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Dataset Card for "hotpot_qa"
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.
{
"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
: astring
feature.question
: astring
feature.answer
: astring
feature.type
: astring
feature.level
: astring
feature.supporting_facts
: a dictionary feature containing:title
: astring
feature.sent_id
: aint32
feature.
context
: a dictionary feature containing:title
: astring
feature.sentences
: alist
ofstring
features.
fullwiki
id
: astring
feature.question
: astring
feature.answer
: astring
feature.type
: astring
feature.level
: astring
feature.supporting_facts
: a dictionary feature containing:title
: astring
feature.sent_id
: aint32
feature.
context
: a dictionary feature containing:title
: astring
feature.sentences
: alist
ofstring
features.
Data Splits
distractor
train | validation | |
---|---|---|
distractor | 90447 | 7405 |
fullwiki
train | validation | test | |
---|---|---|---|
fullwiki | 90447 | 7405 | 7405 |
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.
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, @ghomasHudson for adding this dataset.
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