Graph-based Keyword Planning for Legal Clause Generation from Topics

Sagar Joshi, Sumanth Balaji, Aparna Garimella, Vasudeva Varma


Abstract
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.
Anthology ID:
2022.nllp-1.26
Volume:
Proceedings of the Natural Legal Language Processing Workshop 2022
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates (Hybrid)
Editors:
Nikolaos Aletras, Ilias Chalkidis, Leslie Barrett, Cătălina Goanță, Daniel Preoțiuc-Pietro
Venue:
NLLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
276–286
Language:
URL:
https://aclanthology.org/2022.nllp-1.26
DOI:
10.18653/v1/2022.nllp-1.26
Bibkey:
Cite (ACL):
Sagar Joshi, Sumanth Balaji, Aparna Garimella, and Vasudeva Varma. 2022. Graph-based Keyword Planning for Legal Clause Generation from Topics. In Proceedings of the Natural Legal Language Processing Workshop 2022, pages 276–286, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
Cite (Informal):
Graph-based Keyword Planning for Legal Clause Generation from Topics (Joshi et al., NLLP 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.nllp-1.26.pdf
Video:
 https://aclanthology.org/2022.nllp-1.26.mp4