RAG based Question Answering of Korean Laws and Precedents

Kiho Seo; Takehito Utsuro

doi:10.18653/v1/2025.fever-1.7

RAG based Question Answering of Korean Laws and Precedents

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Abstract

We propose a method of improving the performance of question answering based on the interpretation of criminal law regulations in the Korean language by using large language models. In this study, we develop a system that accumulates legislative texts and case precedents related to criminal procedures published on the Internet.The system searches for relevant legal provisions and precedents related to the queryunder the RAG (Retrieval-Augmented Generation) framework.It generates accurate responses to questions by conducting reasoning through large language modelsbased on these relevant laws and precedents. As an application example of this system, it can be utilized to support decision makingin investigations and legal interpretation scenarios within the field of Korean criminal law.

Anthology ID:: 2025.fever-1.7
Volume:: Proceedings of the Eighth Fact Extraction and VERification Workshop (FEVER)
Month:: July
Year:: 2025
Address:: Vienna, Austria
Editors:: Mubashara Akhtar, Rami Aly, Christos Christodoulopoulos, Oana Cocarascu, Zhijiang Guo, Arpit Mittal, Michael Schlichtkrull, James Thorne, Andreas Vlachos
Venues:: FEVER | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 91–100
Language:
URL:: https://aclanthology.org/2025.fever-1.7/
DOI:: 10.18653/v1/2025.fever-1.7
Bibkey:
Cite (ACL):: Kiho Seo and Takehito Utsuro. 2025. RAG based Question Answering of Korean Laws and Precedents. In Proceedings of the Eighth Fact Extraction and VERification Workshop (FEVER), pages 91–100, Vienna, Austria. Association for Computational Linguistics.
Cite (Informal):: RAG based Question Answering of Korean Laws and Precedents (Seo & Utsuro, FEVER 2025)
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PDF:: https://aclanthology.org/2025.fever-1.7.pdf

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@inproceedings{seo-utsuro-2025-rag,
    title = "{RAG} based Question Answering of {K}orean Laws and Precedents",
    author = "Seo, Kiho  and
      Utsuro, Takehito",
    editor = "Akhtar, Mubashara  and
      Aly, Rami  and
      Christodoulopoulos, Christos  and
      Cocarascu, Oana  and
      Guo, Zhijiang  and
      Mittal, Arpit  and
      Schlichtkrull, Michael  and
      Thorne, James  and
      Vlachos, Andreas",
    booktitle = "Proceedings of the Eighth Fact Extraction and VERification Workshop (FEVER)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.fever-1.7/",
    doi = "10.18653/v1/2025.fever-1.7",
    pages = "91--100",
    ISBN = "978-1-959429-53-1",
    abstract = "We propose a method of improving the performance of question answering based on the interpretation of criminal law regulations in the Korean language by using large language models. In this study, we develop a system that accumulates legislative texts and case precedents related to criminal procedures published on the Internet.The system searches for relevant legal provisions and precedents related to the queryunder the RAG (Retrieval-Augmented Generation) framework.It generates accurate responses to questions by conducting reasoning through large language modelsbased on these relevant laws and precedents. As an application example of this system, it can be utilized to support decision makingin investigations and legal interpretation scenarios within the field of Korean criminal law."
}

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%0 Conference Proceedings
%T RAG based Question Answering of Korean Laws and Precedents
%A Seo, Kiho
%A Utsuro, Takehito
%Y Akhtar, Mubashara
%Y Aly, Rami
%Y Christodoulopoulos, Christos
%Y Cocarascu, Oana
%Y Guo, Zhijiang
%Y Mittal, Arpit
%Y Schlichtkrull, Michael
%Y Thorne, James
%Y Vlachos, Andreas
%S Proceedings of the Eighth Fact Extraction and VERification Workshop (FEVER)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 978-1-959429-53-1
%F seo-utsuro-2025-rag
%X We propose a method of improving the performance of question answering based on the interpretation of criminal law regulations in the Korean language by using large language models. In this study, we develop a system that accumulates legislative texts and case precedents related to criminal procedures published on the Internet.The system searches for relevant legal provisions and precedents related to the queryunder the RAG (Retrieval-Augmented Generation) framework.It generates accurate responses to questions by conducting reasoning through large language modelsbased on these relevant laws and precedents. As an application example of this system, it can be utilized to support decision makingin investigations and legal interpretation scenarios within the field of Korean criminal law.
%R 10.18653/v1/2025.fever-1.7
%U https://aclanthology.org/2025.fever-1.7/
%U https://doi.org/10.18653/v1/2025.fever-1.7
%P 91-100

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Markdown (Informal)

[RAG based Question Answering of Korean Laws and Precedents](https://aclanthology.org/2025.fever-1.7/) (Seo & Utsuro, FEVER 2025)

RAG based Question Answering of Korean Laws and Precedents (Seo & Utsuro, FEVER 2025)

ACL

Kiho Seo and Takehito Utsuro. 2025. RAG based Question Answering of Korean Laws and Precedents. In Proceedings of the Eighth Fact Extraction and VERification Workshop (FEVER), pages 91–100, Vienna, Austria. Association for Computational Linguistics.