Analysing the Resourcefulness of the Paragraph for Precedence Retrieval

TL;DR

This paper investigates the effectiveness of paragraph-level information in legal judgment similarity and precedence retrieval, showing it can outperform baseline document-level methods with fewer interactions.

Contribution

It introduces paragraph-level analysis for legal precedence retrieval, demonstrating improved discriminating power and comparable performance to state-of-the-art methods.

Findings

Paragraph-level methods better capture judgment similarity.

Fewer paragraph interactions needed for effective retrieval.

Comparable performance to existing state-of-the-art approaches.

Abstract

Developing methods for extracting relevant legal information to aid legal practitioners is an active research area. In this regard, research efforts are being made by leveraging different kinds of information, such as meta-data, citations, keywords, sentences, paragraphs, etc. Similar to any text document, legal documents are composed of paragraphs. In this paper, we have analyzed the resourcefulness of paragraph-level information in capturing similarity among judgments for improving the performance of precedence retrieval. We found that the paragraph-level methods could capture the similarity among the judgments with only a few paragraph interactions and exhibit more discriminating power over the baseline document-level method. Moreover, the comparison results on two benchmark datasets for the precedence retrieval on the Indian supreme court judgments task show that the paragraph-level methods exhibit comparable performance with the state-of-the-art methods