Investigating Strategies for Clause Recommendation
This addresses the need for automated legal contract assistance, but it is incremental as it builds on prior work in a niche domain.
The paper tackles the problem of recommending legal clauses for contracts by investigating the importance of similar contracts' representations, focusing on 15 common clause types to improve clause generation as a step toward contract generation.
Clause recommendation is the problem of recommending a clause to a legal contract, given the context of the contract in question and the clause type to which the clause should belong. With not much prior work being done toward the generation of legal contracts, this problem was proposed as a first step toward the bigger problem of contract generation. As an open-ended text generation problem, the distinguishing characteristics of this problem lie in the nature of legal language as a sublanguage and the considerable similarity of textual content within the clauses of a specific type. This similarity aspect in legal clauses drives us to investigate the importance of similar contracts' representation for recommending clauses. In our work, we experiment with generating clauses for 15 commonly occurring clause types in contracts expanding upon the previous work on this problem and analyzing clause recommendations in varying settings using information derived from similar contracts.