Hugging Face's logo

Datasets:
KorQuAD
/
squad_kor_v2

Tasks:
Question Answering
Sub-tasks:
extractive-qa
Languages:
Korean
Size:
10K<n<100K
License:
Dataset card Files Community
3
Dataset Viewer
Full Screen

The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider removing the loading script and relying on automated data support (you can use convert_to_parquet from the datasets library). If this is not possible, please open a discussion for direct help.

Dataset Card for KorQuAD v2.1

Dataset Summary

KorQuAD 2.0 is a Korean question and answering dataset consisting of a total of 100,000+ pairs. There are three major differences from KorQuAD 1.0, which is the standard Korean Q & A data. The first is that a given document is a whole Wikipedia page, not just one or two paragraphs. Second, because the document also contains tables and lists, it is necessary to understand the document structured with HTML tags. Finally, the answer can be a long text covering not only word or phrase units, but paragraphs, tables, and lists.

Supported Tasks and Leaderboards

question-answering

Languages

Korean

Dataset Structure

Follows the standart SQuAD format. There is only 1 answer per question

Data Instances

An example from the data set looks as follows:

{'answer': {'answer_start': 3873,
  'html_answer_start': 16093,
  'text': '20,890 ํ‘œ'},
 'context': '<!DOCTYPE html>\n<html>\n<head>\n<meta>\n<title>์‹ฌ๊ทœ์–ธ - ์œ„ํ‚ค๋ฐฑ๊ณผ, ์šฐ๋ฆฌ ๋ชจ๋‘์˜ ๋ฐฑ๊ณผ์‚ฌ์ „</title>\n\n\n<link>\n.....[omitted]',
 'id': '36615',
 'question': '์‹ฌ๊ทœ์–ธ์€ 17๋Œ€ ์ง€๋ฐฉ ์„ ๊ฑฐ์—์„œ ๋ช‡ ํ‘œ๋ฅผ ๋“ํ‘œํ•˜์˜€๋Š”๊ฐ€?',
 'raw_html': '<!DOCTYPE html>\n<html c ...[omitted]',
 'title': '์‹ฌ๊ทœ์–ธ',
 'url': 'https://ko.wikipedia.org/wiki/์‹ฌ๊ทœ์–ธ'}

Data Fields 

{'id': Value(dtype='string', id=None),
 'title': Value(dtype='string', id=None),
 'context': Value(dtype='string', id=None),
 'question': Value(dtype='string', id=None),
 'answer': {'text': Value(dtype='string', id=None),
  'answer_start': Value(dtype='int32', id=None),
  'html_answer_start': Value(dtype='int32', id=None)},
 'url': Value(dtype='string', id=None),
 'raw_html': Value(dtype='string', id=None)}

Data Splits

  • Train : 83486
  • Validation: 10165

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Wikipedia

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

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

[More Information Needed]

Licensing Information

CC BY-ND 2.0 KR

Citation Information 

@article{NODE09353166,
    author={Youngmin Kim,Seungyoung Lim;Hyunjeong Lee;Soyoon Park;Myungji Kim},
    title={{KorQuAD 2.0: Korean QA Dataset for Web Document Machine Comprehension}},
    booltitle={{Journal of KIISE ์ œ47๊ถŒ ์ œ6ํ˜ธ}},
    journal={{Journal of KIISE}},
    volume={{47}},
    issue={{6}},
    publisher={The Korean Institute of Information Scientists and Engineers},
    year={2020},
    ISSN={{2383-630X}},
    pages={577-586},
    url={http://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE09353166}}

Contributions

Thanks to @cceyda for adding this dataset.

Downloads last month
181
**Homepage**
**Homepage**
**Repository**
**Repository**
**Paper**
**Paper**

Models trained or fine-tuned on KorQuAD/squad_kor_v2