Legal contracts, such as employment or lease agreements, are important documents as they govern the obligations and entitlements of the various contracting parties. However, these documents are typically long and written in legalese resulting in lots of manual hours spent in understanding them. In this paper, we address the task of summarizing legal contracts for each of the contracting parties, to enable faster reviewing and improved understanding of them. Specifically, we collect a dataset consisting of pairwise importance comparison annotations by legal experts for ~293K sentence pairs from lease agreements. We propose a novel extractive summarization system to automatically produce a summary consisting of the most important obligations, entitlements, and prohibitions in a contract. It consists of two modules: (1) a content categorize to identify sentences containing each of the categories (i.e., obligation, entitlement, and prohibition) for a party, and (2) an importance ranker to compare the importance among sentences of each category for a party to obtain a ranked list. The final summary is produced by selecting the most important sentences of a category for each of the parties. We demonstrate the effectiveness of our proposed system by comparing it against several text ranking baselines via automatic and human evaluation.
翻译:法律合同,如雇用或租赁协议,是重要文件,因为它们规范了合同各方的义务和应享权利,然而,这些文件一般都是长长的、用法律文字写成的,导致大量人工时间来理解这些合同。在本文件中,我们处理的是总结每个合同方的法律合同的任务,以便能够更快地审查和增进对这些合同的理解。具体地说,我们收集一套数据集,由法律专家对租赁协议中的~293K对判决进行对等的重要性比较,由法律专家对~293K判决的说明组成。我们建议一个新的采掘总结系统,自动产生一份摘要,包括最重要的义务、应享权利和合同中的禁令。它由两个模块组成:(1) 内容分类,确定载有每一类(即义务、应享权利和禁令)对一方的判决,以及(2) 重要等级,将每一类判决对一方的重要性进行比较,以便获得一份分级清单。最后摘要是挑选每一类当事方最重要的判决。我们通过自动和人力评价将其与若干文本排序基线加以比较,以表明我们提议的系统的有效性。