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

翻译：开发提取相关法律信息以辅助法律从业者的方法是一个活跃的研究领域。在此方面，研究人员通过利用不同类型的资源（如元数据、引用、关键词、句子、段落等）开展相关工作。与任何文本文件类似，法律文件由段落构成。本文分析了段落级信息在捕捉判决书相似性以提升先例检索性能方面的资源价值。研究发现，段落级方法仅通过少量段落交互即可捕捉判决书之间的相似性，且相较于基准文档级方法具有更强的区分能力。此外，在印度最高法院判决先例检索的两个基准数据集上的对比结果表明，段落级方法展现出与最先进方法相当的性能。