Generating domain-specific content such as legal clauses based on minimal user-provided information can be of significant benefit in automating legal contract generation. In this paper, we propose a controllable graph-based mechanism that can generate legal clauses using only the topic or type of the legal clauses. Our pipeline consists of two stages involving a graph-based planner followed by a clause generator. The planner outlines the content of a legal clause as a sequence of keywords in the order of generic to more specific clause information based on the input topic using a controllable graph-based mechanism. The generation stage takes in a given plan and generates a clause. The pipeline consists of a graph-based planner followed by text generation. We illustrate the effectiveness of our proposed two-stage approach on a broad set of clause topics in contracts.
Cite
@article{arxiv.2301.06901,
title = {Graph-based Keyword Planning for Legal Clause Generation from Topics},
author = {Sagar Joshi and Sumanth Balaji and Aparna Garimella and Vasudeva Varma},
journal= {arXiv preprint arXiv:2301.06901},
year = {2023}
}
Comments
To be published in the Natural Legal Language Processing Workshop, EMNLP 2022 (11 pages, 7 figures)