Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Sub-tasks:
extractive-qa
Languages:
Korean
Size:
10K - 100K
ArXiv:
License:
metadata
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 Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
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': ['κ΅ν₯곑']},
'context': '1839λ
λ°κ·Έλλ κ΄΄ν
μ νμ°μ€νΈμ μ²μ μ½κ³ κ·Έ λ΄μ©μ λ§μμ΄ λλ € μ΄λ₯Ό μμ¬λ‘ ν΄μ νλμ κ΅ν₯곑μ μ°λ €λ λ»μ κ°λλ€. μ΄ μκΈ° λ°κ·Έλλ 1838λ
μ λΉ λ
μ΄μΌλ‘ μ°μ μμ μ λ€ κ±²μ μν©μ΄λΌ μ’μ κ³Ό μ€λ§μ κ°λνμΌλ©° λ©νΌμ€ν ν λ μ€λ₯Ό λ§λλ νμ°μ€νΈμ μ¬κ²½μ 곡κ°νλ€κ³ νλ€. λν ν리μμ μλΈλ€ν¬μ μ§νλ‘ ν리 μμ
μ κ΄νμ
λ¨μ΄ μ°μ£Όνλ λ² ν λ²€μ κ΅ν₯곑 9λ²μ λ£κ³ κΉμ κ°λͺ
μ λ°μλλ°, μ΄κ²μ΄ μ΄λ¬ν΄ 1μμ νμ°μ€νΈμ μ곑μΌλ‘ μ°μ¬μ§ μ΄ μνμ μ‘°κΈμ΄λΌλ μν₯μ λΌμ³€μΌλ¦¬λΌλ κ²μ μμ¬ν μ¬μ§κ° μλ€. μ¬κΈ°μ λΌλ¨μ‘° μ‘°μ±μ κ²½μ°μλ κ·Έμ μ κΈ°μ μ ν μλ κ²μ²λΌ λ¨μν μ μ μ νΌλ‘λ μ€μκ° λ°μλ κ²μ΄ μλλΌ λ² ν λ²€μ ν©μ°½κ΅ν₯곑 μ‘°μ±μ μν₯μ λ°μ κ²μ λ³Ό μ μλ€. κ·Έλ κ² κ΅ν₯곑 μ곑μ 1839λ
λΆν° 40λ
μ κ±Έμ³ ν리μμ μ°©μνμΌλ 1μ
μ₯μ μ΄ λ€μ μ€λ¨νλ€. λν μνμ μμ±κ³Ό λμμ κ·Έλ μ΄ μ곑(1μ
μ₯)μ ν리 μμ
μμ μ°μ£Όνμμ μ°μ£Όν ννΈλ³΄κΉμ§ μ€λΉνμμΌλ, μ€μ λ‘λ μ΄λ£¨μ΄μ§μ§λ μμλ€. κ²°κ΅ μ΄μ°μ 4λ
λ°μ΄ μ§λ νμ λλ μ€λ΄μμ μ°μ£Όλμκ³ μ¬μ°λ μ΄λ£¨μ΄μ‘μ§λ§, μ΄νμ κ·Έλλ‘ λ°©μΉλκ³ λ§μλ€. κ·Έ μ¬μ΄μ κ·Έλ 리μμΉμ λ°©ν©νλ λ€λλλμΈμ μμ±νκ³ ννΈμ΄μ μλ μ°©μνλ λ± λΆμ£Όν μκ°μ 보λλλ°, κ·Έλ° λ°μ μνμ΄ μ΄ κ³‘μ μκ² ν κ²μ΄ μλκ° νλ μ견λ μλ€.',
'id': '6566495-0-0',
'question': 'λ°κ·Έλλ κ΄΄ν
μ νμ°μ€νΈλ₯Ό μ½κ³ 무μμ μ°κ³ μ νλκ°?',
'title': 'νμ°μ€νΈ_μ곑'}
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
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 for adding this dataset.