RAG based Question Answering of Korean Laws and Precedents

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 query under the RAG (Retrieval-Augmented Generation) framework.It generates accurate responses to questions by conducting reasoning through large language models based on these relevant laws and precedents.As an application example of this system, it can be utilized to support decision making in investigations and legal interpretation scenarios within the field of Korean criminal law.