Myanmar Law Cases and Proceedings Retrieval with GraphRAG

Legal document retrieval poses various challenges due to diverse linguistic and domain-specific complexities. The GraphRAG approach represents a significant advance in retrieving and summarizing archival case documents. It deals with the difficulties of accessing relevant legal information with inherent complexities. Further, it improves the efficiency of information retrieval by using graphical representations of legal texts. It enables lawyers to navigate the complex relationships between cases, statutes, and legal principles. The framework facilitates extracting relevant information and incorporates advanced natural language processing techniques for efficient summarization. It enables users to understand key legal concepts quickly. By fostering interdisciplinary collaboration and focusing on user-centered design, GraphRAG can significantly improve access to legal information, thereby meeting the growing needs of the legal community. This paper proposes a graph-rag-based approach for multilingual legal information retrieval (ML2IR), focusing on the Burmese language. Our graph-rag-based approach addresses the hallucination problem, crucial in legal information retrieval. Additionally, our work identifies important nodes and establishes contextual relationships, leading to higher accuracy and effective information retrieval.

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Publication Details

Published
2024-12-15
DOI
https://doi.org/10.1109/bigdata62323.2024.10825155
Citations
1
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
0.35
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Myanmar Law Cases and Proceedings Retrieval with GraphRAG

Parag Kulkarni, Shoon Lei Phyu, Shuhayel Jaman, Murataly Uchkempirov
1 citations
Topic Modeling
0.35
article

Myanmar Law Cases and Proceedings Retrieval with GraphRAG

Parag Kulkarni, Shoon Lei Phyu, Shuhayel Jaman, Murataly Uchkempirov
article en
1 citations

Abstract

Legal document retrieval poses various challenges due to diverse linguistic and domain-specific complexities. The GraphRAG approach represents a significant advance in retrieving and summarizing archival case documents. It deals with the difficulties of accessing relevant legal information with inherent complexities. Further, it improves the efficiency of information retrieval by using graphical representations of legal texts. It enables lawyers to navigate the complex relationships between cases, statutes, and legal principles. The framework facilitates extracting relevant information and incorporates advanced natural language processing techniques for efficient summarization. It enables users to understand key legal concepts quickly. By fostering interdisciplinary collaboration and focusing on user-centered design, GraphRAG can significantly improve access to legal information, thereby meeting the growing needs of the legal community. This paper proposes a graph-rag-based approach for multilingual legal information retrieval (ML2IR), focusing on the Burmese language. Our graph-rag-based approach addresses the hallucination problem, crucial in legal information retrieval. Additionally, our work identifies important nodes and establishes contextual relationships, leading to higher accuracy and effective information retrieval.

Tokyo International University (JP)
Peace, Justice and strong institutions
Openalex Percentile: Top 30%
Topic Modeling
0.35
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