Advancements in legal text summarization: integrating InLegalBERT for effective extractive summarization

Saloni Sharma () and Piyush Pratap Singh ()
Additional contact information
Saloni Sharma: Jawaharlal Nehru University
Piyush Pratap Singh: Jawaharlal Nehru University

International Journal of System Assurance Engineering and Management, 2025, vol. 16, issue 4, No 3, 1382-1397

Abstract: Abstract Indian court judgment reports frequently include complicated words and sentences, making it difficult for the general public and legal experts to understand these documents. Legal organizations hire legal experts to summarize complex and lengthy legal texts. Hence, a variety of techniques have been created to construct the summaries. This study investigates the application of InLegalBERT, a pre-trained legal language model, for summarizing Indian legal documents. We propose a novel framework that utilizes InLegalBERT’s sentence embeddings combined with K-Means clustering to extract and prioritize legally significant information for generating concise summaries. Unlike traditional methods, our approach integrates domain-specific knowledge to enhance the accuracy and relevance of summaries. The framework was evaluated at compression ratios of 10%, 20%, and 30%, and benchmarked against five models: Legal Pegasus, T5 base, BART, BERT, and ChatGPT. At a 30% compression ratio, our method outperformed others with a ROUGE-L F1 score of 0.3858, precision of 0.3585, recall of 0.4526, and a beta score of 0.4481. Additionally, qualitative evaluation using Krippendorff’s Alpha confirmed the consistency and reliability of the summaries.

Keywords: BART; BERT; Clustering; InLegalBERT; K-Means; Legal case summarization; Legal Pegasus; T5 base (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s13198-025-02783-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ijsaem:v:16:y:2025:i:4:d:10.1007_s13198-025-02783-8

Ordering information: This journal article can be ordered from
http://www.springer.com/engineering/journal/13198

DOI: 10.1007/s13198-025-02783-8

Access Statistics for this article

International Journal of System Assurance Engineering and Management is currently edited by P.K. Kapur, A.K. Verma and U. Kumar

More articles in International Journal of System Assurance Engineering and Management from Springer, The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().