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---
annotations_creators:
- crowdsourced
language_creators:
- found
languages:
- ko
licenses:
- cc-by-nd-2-0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractive-qa
paperswithcode_id: korquad
pretty_name: The Korean Question Answering Dataset
---
# Dataset Card for KorQuAD v1.0
## 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://korquad.github.io/KorQuad%201.0/)
- [**Repository:**](https://github.com/korquad/korquad.github.io/tree/master/dataset)
- [**Paper:**](https://arxiv.org/abs/1909.07005)
### Dataset Summary
KorQuAD 1.0 is a large-scale question-and-answer dataset constructed for Korean machine reading comprehension, and investigate the dataset to understand the distribution of answers and the types of reasoning required to answer the question. This dataset benchmarks the data generating process of SQuAD v1.0 to meet the standard.
### Supported Tasks and Leaderboards
`question-answering`
### Languages
Korean
## Dataset Structure
Follows the standars SQuAD format.
### Data Instances
An example from the data set looks as follows:
```
{'answers': {'answer_start': [54], 'text': ['ꡐν–₯곑']},
'context': '1839λ…„ λ°”κ·Έλ„ˆλŠ” κ΄΄ν…Œμ˜ νŒŒμš°μŠ€νŠΈμ„ 처음 읽고 κ·Έ λ‚΄μš©μ— 마음이 끌렀 이λ₯Ό μ†Œμž¬λ‘œ ν•΄μ„œ ν•˜λ‚˜μ˜ ꡐν–₯곑을 μ“°λ €λŠ” λœ»μ„ κ°–λŠ”λ‹€. 이 μ‹œκΈ° λ°”κ·Έλ„ˆλŠ” 1838년에 λΉ› λ…μ΄‰μœΌλ‘œ μ‚°μ „μˆ˜μ „μ„ λ‹€ 걲은 상황이라 쒌절과 싀망에 κ°€λ“ν–ˆμœΌλ©° λ©”ν”ΌμŠ€ν† νŽ λ ˆμŠ€λ₯Ό λ§Œλ‚˜λŠ” 파우슀트의 심경에 κ³΅κ°ν–ˆλ‹€κ³  ν•œλ‹€. λ˜ν•œ νŒŒλ¦¬μ—μ„œ μ•„λΈŒλ„€ν¬μ˜ μ§€νœ˜λ‘œ 파리 μŒμ•…μ› κ΄€ν˜„μ•…λ‹¨μ΄ μ—°μ£Όν•˜λŠ” λ² ν† λ²€μ˜ ꡐν–₯곑 9λ²ˆμ„ λ“£κ³  κΉŠμ€ 감λͺ…을 λ°›μ•˜λŠ”λ°, 이것이 이듬해 1월에 파우슀트의 μ„œκ³‘μœΌλ‘œ 쓰여진 이 μž‘ν’ˆμ— μ‘°κΈˆμ΄λΌλ„ 영ν–₯을 λΌμ³€μœΌλ¦¬λΌλŠ” 것은 μ˜μ‹¬ν•  여지가 μ—†λ‹€. μ—¬κΈ°μ˜ 라단쑰 μ‘°μ„±μ˜ κ²½μš°μ—λ„ 그의 전기에 μ ν˜€ μžˆλŠ” κ²ƒμ²˜λŸΌ λ‹¨μˆœν•œ 정신적 ν”Όλ‘œλ‚˜ μ‹€μ˜κ°€ 반영된 것이 μ•„λ‹ˆλΌ λ² ν† λ²€μ˜ 합창ꡐν–₯곑 μ‘°μ„±μ˜ 영ν–₯을 받은 것을 λ³Ό 수 μžˆλ‹€. κ·Έλ ‡κ²Œ ꡐν–₯곑 μž‘κ³‘μ„ 1839λ…„λΆ€ν„° 40년에 걸쳐 νŒŒλ¦¬μ—μ„œ μ°©μˆ˜ν–ˆμœΌλ‚˜ 1μ•…μž₯을 μ“΄ 뒀에 μ€‘λ‹¨ν–ˆλ‹€. λ˜ν•œ μž‘ν’ˆμ˜ μ™„μ„±κ³Ό λ™μ‹œμ— κ·ΈλŠ” 이 μ„œκ³‘(1μ•…μž₯)을 파리 μŒμ•…μ›μ˜ μ—°μ£ΌνšŒμ—μ„œ μ—°μ£Όν•  νŒŒνŠΈλ³΄κΉŒμ§€ μ€€λΉ„ν•˜μ˜€μœΌλ‚˜, μ‹€μ œλ‘œλŠ” μ΄λ£¨μ–΄μ§€μ§€λŠ” μ•Šμ•˜λ‹€. κ²°κ΅­ μ΄ˆμ—°μ€ 4λ…„ 반이 μ§€λ‚œ 후에 λ“œλ ˆμŠ€λ΄μ—μ„œ μ—°μ£Όλ˜μ—ˆκ³  μž¬μ—°λ„ μ΄λ£¨μ–΄μ‘Œμ§€λ§Œ, 이후에 κ·ΈλŒ€λ‘œ 방치되고 λ§μ•˜λ‹€. κ·Έ 사이에 κ·ΈλŠ” λ¦¬μ—”μΉ˜μ™€ λ°©ν™©ν•˜λŠ” λ„€λœλž€λ“œμΈμ„ μ™„μ„±ν•˜κ³  νƒ„ν˜Έμ΄μ €μ—λ„ μ°©μˆ˜ν•˜λŠ” λ“± λΆ„μ£Όν•œ μ‹œκ°„μ„ λ³΄λƒˆλŠ”λ°, 그런 λ°”μœ μƒν™œμ΄ 이 곑을 잊게 ν•œ 것이 μ•„λ‹Œκ°€ ν•˜λŠ” μ˜κ²¬λ„ μžˆλ‹€.',
'id': '6566495-0-0',
'question': 'λ°”κ·Έλ„ˆλŠ” κ΄΄ν…Œμ˜ 파우슀트λ₯Ό 읽고 무엇을 μ“°κ³ μž ν–ˆλŠ”κ°€?',
'title': '파우슀트_μ„œκ³‘'}
```
### 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),
'answers': Sequence(feature={'text': Value(dtype='string', id=None), 'answer_start': Value(dtype='int32', id=None)}, length=-1, id=None)}
```
### Data Splits
- Train: 60407
- Validation: 5774
## 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](https://creativecommons.org/licenses/by-nd/2.0/kr/deed.en)
### Citation Information
```
@article{lim2019korquad1,
title={Korquad1. 0: Korean qa dataset for machine reading comprehension},
author={Lim, Seungyoung and Kim, Myungji and Lee, Jooyoul},
journal={arXiv preprint arXiv:1909.07005},
year={2019}
```
### Contributions
Thanks to [@cceyda](https://github.com/cceyda) for adding this dataset.