multi_re_qa / README.md
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---
annotations_creators:
- expert-generated
- found
language_creators:
- expert-generated
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
- 10K<n<100K
- 1K<n<10K
- 1M<n<10M
source_datasets:
- extended|other-BioASQ
- extended|other-DuoRC
- extended|other-HotpotQA
- extended|other-Natural-Questions
- extended|other-Relation-Extraction
- extended|other-SQuAD
- extended|other-SearchQA
- extended|other-TextbookQA
- extended|other-TriviaQA
task_categories:
- question-answering
task_ids:
- extractive-qa
- open-domain-qa
paperswithcode_id: multireqa
pretty_name: MultiReQA
dataset_info:
- config_name: SearchQA
features:
- name: candidate_id
dtype: string
- name: response_start
dtype: int32
- name: response_end
dtype: int32
splits:
- name: train
num_bytes: 183902877
num_examples: 3163801
- name: validation
num_bytes: 26439174
num_examples: 454836
download_size: 36991959
dataset_size: 210342051
- config_name: TriviaQA
features:
- name: candidate_id
dtype: string
- name: response_start
dtype: int32
- name: response_end
dtype: int32
splits:
- name: train
num_bytes: 107326326
num_examples: 1893674
- name: validation
num_bytes: 13508062
num_examples: 238339
download_size: 21750402
dataset_size: 120834388
- config_name: HotpotQA
features:
- name: candidate_id
dtype: string
- name: response_start
dtype: int32
- name: response_end
dtype: int32
splits:
- name: train
num_bytes: 29516866
num_examples: 508879
- name: validation
num_bytes: 3027229
num_examples: 52191
download_size: 6343389
dataset_size: 32544095
- config_name: SQuAD
features:
- name: candidate_id
dtype: string
- name: response_start
dtype: int32
- name: response_end
dtype: int32
splits:
- name: train
num_bytes: 16828974
num_examples: 95659
- name: validation
num_bytes: 2012997
num_examples: 10642
download_size: 3003646
dataset_size: 18841971
- config_name: NaturalQuestions
features:
- name: candidate_id
dtype: string
- name: response_start
dtype: int32
- name: response_end
dtype: int32
splits:
- name: train
num_bytes: 28732767
num_examples: 448355
- name: validation
num_bytes: 1418124
num_examples: 22118
download_size: 6124487
dataset_size: 30150891
- config_name: BioASQ
features:
- name: candidate_id
dtype: string
- name: response_start
dtype: int32
- name: response_end
dtype: int32
splits:
- name: test
num_bytes: 766190
num_examples: 14158
download_size: 156649
dataset_size: 766190
- config_name: RelationExtraction
features:
- name: candidate_id
dtype: string
- name: response_start
dtype: int32
- name: response_end
dtype: int32
splits:
- name: test
num_bytes: 217870
num_examples: 3301
download_size: 73019
dataset_size: 217870
- config_name: TextbookQA
features:
- name: candidate_id
dtype: string
- name: response_start
dtype: int32
- name: response_end
dtype: int32
splits:
- name: test
num_bytes: 4182675
num_examples: 71147
download_size: 704602
dataset_size: 4182675
- config_name: DuoRC
features:
- name: candidate_id
dtype: string
- name: response_start
dtype: int32
- name: response_end
dtype: int32
splits:
- name: test
num_bytes: 1483518
num_examples: 5525
download_size: 97625
dataset_size: 1483518
config_names:
- BioASQ
- DuoRC
- HotpotQA
- NaturalQuestions
- RelationExtraction
- SQuAD
- SearchQA
- TextbookQA
- TriviaQA
---
# Dataset Card for MultiReQA
## 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://github.com/google-research-datasets/MultiReQA
- **Repository:** https://github.com/google-research-datasets/MultiReQA
- **Paper:** https://arxiv.org/pdf/2005.02507.pdf
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
MultiReQA contains the sentence boundary annotation from eight publicly available QA datasets including SearchQA, TriviaQA, HotpotQA, NaturalQuestions, SQuAD, BioASQ, RelationExtraction, and TextbookQA. Five of these datasets, including SearchQA, TriviaQA, HotpotQA, NaturalQuestions, SQuAD, contain both training and test data, and three, in cluding BioASQ, RelationExtraction, TextbookQA, contain only the test data (also includes DuoRC but not specified in the official documentation)
### Supported Tasks and Leaderboards
- Question answering (QA)
- Retrieval question answering (ReQA)
### Languages
Sentence boundary annotation for SearchQA, TriviaQA, HotpotQA, NaturalQuestions, SQuAD, BioASQ, RelationExtraction, TextbookQA and DuoRC
## Dataset Structure
### Data Instances
The general format is:
`
{
"candidate_id": <candidate_id>,
"response_start": <response_start>,
"response_end": <response_end>
}
...
`
An example from SearchQA:
`{'candidate_id': 'SearchQA_000077f3912049dfb4511db271697bad/_0_1',
'response_end': 306,
'response_start': 243} `
### Data Fields
`
{
"candidate_id": <STRING>,
"response_start": <INT>,
"response_end": <INT>
}
...
`
- **candidate_id:** The candidate id of the candidate sentence. It consists of the original qid from the MRQA shared task.
- **response_start:** The start index of the sentence with respect to its original context.
- **response_end:** The end index of the sentence with respect to its original context
### Data Splits
Train and Dev splits are available only for the following datasets,
- SearchQA
- TriviaQA
- HotpotQA
- SQuAD
- NaturalQuestions
Test splits are available only for the following datasets,
- BioASQ
- RelationExtraction
- TextbookQA
The number of candidate sentences for each dataset in the table below.
| | MultiReQA | |
|--------------------|-----------|---------|
| | train | test |
| SearchQA | 629,160 | 454,836 |
| TriviaQA | 335,659 | 238,339 |
| HotpotQA | 104,973 | 52,191 |
| SQuAD | 87,133 | 10,642 |
| NaturalQuestions | 106,521 | 22,118 |
| BioASQ | - | 14,158 |
| RelationExtraction | - | 3,301 |
| TextbookQA | - | 3,701 |
## Dataset Creation
### Curation Rationale
MultiReQA is a new multi-domain ReQA evaluation suite composed of eight retrieval QA tasks drawn from publicly available QA datasets from the [MRQA shared task](https://mrqa.github.io/). The dataset was curated by converting existing QA datasets from [MRQA shared task](https://mrqa.github.io/) to the format of MultiReQA benchmark.
### Source Data
#### Initial Data Collection and Normalization
The Initial data collection was performed by converting existing QA datasets from MRQA shared task to the format of MultiReQA benchmark.
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
The annotators/curators of the dataset are [mandyguo-xyguo](https://github.com/mandyguo-xyguo) and [mwurts4google](https://github.com/mwurts4google), the contributors of the official MultiReQA github repository
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
The annotators/curators of the dataset are [mandyguo-xyguo](https://github.com/mandyguo-xyguo) and [mwurts4google](https://github.com/mwurts4google), the contributors of the official MultiReQA github repository
### Licensing Information
[More Information Needed]
### Citation Information
```
@misc{m2020multireqa,
title={MultiReQA: A Cross-Domain Evaluation for Retrieval Question Answering Models},
author={Mandy Guo and Yinfei Yang and Daniel Cer and Qinlan Shen and Noah Constant},
year={2020},
eprint={2005.02507},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
### Contributions
Thanks to [@Karthik-Bhaskar](https://github.com/Karthik-Bhaskar) for adding this dataset.