Graph-based Keyword Planning for Legal Clause Generation from Topics
This addresses automating legal contract generation for legal professionals, but it is incremental as it builds on existing text generation methods with a domain-specific adaptation.
The paper tackled generating legal clauses from minimal user input by proposing a two-stage pipeline with a graph-based planner and a clause generator, achieving effectiveness across a broad set of clause topics in contracts.
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.