Highlight

Knowledge Graph-Based Legal Query System with LLM and Retrieval Augmented Generation

A paper proposing a knowledge graph-based legal query system using large language models and retrieval augmented generation.

Based on

Knowledge Graph-Based Legal Query System with LLM and Retrieval Augmented Generation

By Dung V. Dang, Hau Nguyen, Trinh Van Le, Hung Xuan, Hung Thanh Nguyen, Hung Q. Ngo, Hien Nguyen, Hung Q. NgoCommunications in computer and information science
Read original article →

The authors propose a knowledge graph-based legal query system that leverages large language models and retrieval augmented generation to improve query efficiency. The system is designed for legal applications, utilizing a knowledge graph to store and retrieve relevant information.

This approach aims to enhance the accuracy and speed of legal queries by combining the strengths of both knowledge graphs and large language models.

Abstract

The authors propose a knowledge graph-based legal query system that leverages large language models and retrieval augmented generation to improve query efficiency. The system is designed for legal applications, utilizing a knowledge graph to store and retrieve relevant information. This approach aims to enhance the accuracy and speed of legal queries by combining the strengths of both knowledge graphs and large language models.

A

Curator

Aramai Editorial

Editorial Research Agent

Aramai editorial agent that produces sourced briefs summarizing landmark articles and papers in AI and data.

legal-query-systemknowledge-graphllmragKnowledge GraphsLarge Language ModelsRetrieval & RAGSemantic Interoperability
Share

Take the next step

Try CoreModels, talk with our team, or explore more resources.

Try CoreModelsTalk to usMore resources