发表机构
Lancaster University（兰卡斯特大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对现有先例检索以文档为单位、粒度粗糙的问题，构建了英国判例法段落级先例检索基准UK-PRBench，评估了先进检索模型，证明该任务仍有较大提升空间。
AI 中文摘要
先前判例检索（PCR）旨在识别与给定查询案件相关的先例案件。现有的PCR基准和方法主要在文档级别上操作，将整个判决视为相关性的单位。这种表述对法律从业者来说并非最优，因为判决涉及多个法律问题，而只有一小部分段落与特定查询相关。针对这一空白，我们引入了UK-PRBench，一个用于英国判例法中段落级先例检索的基准，该基准基于从英国国家档案馆获取的判决构建，覆盖了广泛的英国法院和法庭。此外，我们评估了最先进的检索模型并建立了基线结果。我们的实验表明，段落级先例检索对当前的检索方法仍然具有挑战性，凸显了巨大的改进空间。UK-PRBench为评估细粒度先例检索和推进英国法律领域的检索系统提供了一个标准化基准。
英文摘要
Prior case retrieval (PCR) aims to identify precedent cases relevant to a given query case. Existing PCR benchmarks and methods predominantly operate at the document level, treating entire judgments as the unit of relevance. This formulation is suboptimal for legal practitioners, as judgments address multiple legal issues and only a small subset of paragraphs is relevant to a particular query. Addressing this gap, we introduce UK-PRBench, a benchmark for paragraph-level precedent retrieval in UK case law, constructed from judgments obtained from the UK National Archives and covering a broad range of UK courts and tribunals. Furthermore, we evaluate state-of-the-art retrieval models and establish baseline results. Our experiments show that paragraph-level precedent retrieval remains challenging for current retrieval approaches, highlighting substantial room for improvement. UK-PRBench provides a standardised benchmark for evaluating fine-grained precedent retrieval and advancing retrieval systems for the UK legal domain.
