Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Sub-tasks:
open-domain-qa
Languages:
English
Size:
10K - 100K
License:
metadata
paperswithcode_id: wikiqa
Dataset Card for "wiki_qa"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://www.microsoft.com/en-us/download/details.aspx?id=52419
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 6.77 MB
- Size of the generated dataset: 6.10 MB
- Total amount of disk used: 12.87 MB
Dataset Summary
Wiki Question Answering corpus from Microsoft
Supported Tasks and Leaderboards
Languages
Dataset Structure
We show detailed information for up to 5 configurations of the dataset.
Data Instances
default
- Size of downloaded dataset files: 6.77 MB
- Size of the generated dataset: 6.10 MB
- Total amount of disk used: 12.87 MB
An example of 'train' looks as follows.
{
"answer": "Glacier caves are often called ice caves , but this term is properly used to describe bedrock caves that contain year-round ice.",
"document_title": "Glacier cave",
"label": 0,
"question": "how are glacier caves formed?",
"question_id": "Q1"
}
Data Fields
The data fields are the same among all splits.
default
question_id: astringfeature.question: astringfeature.document_title: astringfeature.answer: astringfeature.label: a classification label, with possible values including0(0),1(1).
Data Splits
| name | train | validation | test |
|---|---|---|---|
| default | 20360 | 2733 | 6165 |
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
Citation Information
@InProceedings{YangYihMeek:EMNLP2015:WikiQA,
author = {{Yi}, Yang and {Wen-tau}, Yih and {Christopher} Meek},
title = "{WikiQA: A Challenge Dataset for Open-Domain Question Answering}",
journal = {Association for Computational Linguistics},
year = 2015,
doi = {10.18653/v1/D15-1237},
pages = {2013–2018},
}
Contributions
Thanks to @patrickvonplaten, @mariamabarham, @lewtun, @thomwolf for adding this dataset.