CLDec 19, 2022

What to Read in a Contract? Party-Specific Summarization of Legal Obligations, Entitlements, and Prohibitions

arXiv:2212.09825v2134 citationsh-index: 25
Originality Synthesis-oriented
AI Analysis

This addresses the need for faster and improved comprehension of rights and duties in legal contracts for parties involved, representing a domain-specific incremental advancement.

The paper tackles the problem of tedious contract review by proposing party-specific extractive summarization of legal obligations, entitlements, and prohibitions, resulting in a system trained on a dataset of ~293K sentence pairs annotated by legal experts and evaluated against baselines.

Reviewing and comprehending key obligations, entitlements, and prohibitions in legal contracts can be a tedious task due to their length and domain-specificity. Furthermore, the key rights and duties requiring review vary for each contracting party. In this work, we propose a new task of party-specific extractive summarization for legal contracts to facilitate faster reviewing and improved comprehension of rights and duties. To facilitate this, we curate a dataset comprising of party-specific pairwise importance comparisons annotated by legal experts, covering ~293K sentence pairs that include obligations, entitlements, and prohibitions extracted from lease agreements. Using this dataset, we train a pairwise importance ranker and propose a pipeline-based extractive summarization system that generates a party-specific contract summary. We establish the need for incorporating domain-specific notion of importance during summarization by comparing our system against various baselines using both automatic and human evaluation methods

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