ClauseRec: A Clause Recommendation Framework for AI-aided Contract Authoring

Vinay Aggarwal, Aparna Garimella, Balaji Vasan Srinivasan, Anandhavelu N, Rajiv Jain


Abstract
Contracts are a common type of legal document that frequent in several day-to-day business workflows. However, there has been very limited NLP research in processing such documents, and even lesser in generating them. These contracts are made up of clauses, and the unique nature of these clauses calls for specific methods to understand and generate such documents. In this paper, we introduce the task of clause recommendation, as a first step to aid and accelerate the authoring of contract documents. We propose a two-staged pipeline to first predict if a specific clause type is relevant to be added in a contract, and then recommend the top clauses for the given type based on the contract context. We pre-train BERT on an existing library of clauses with two additional tasks and use it for our prediction and recommendation. We experiment with classification methods and similarity-based heuristics for clause relevance prediction, and generation-based methods for clause recommendation, and evaluate the results from various methods on several clause types. We provide analyses on the results, and further outline the limitations and future directions of this line of research.
Anthology ID:
2021.emnlp-main.691
Volume:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2021
Address:
Online and Punta Cana, Dominican Republic
Editors:
Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
8770–8776
Language:
URL:
https://aclanthology.org/2021.emnlp-main.691
DOI:
10.18653/v1/2021.emnlp-main.691
Bibkey:
Cite (ACL):
Vinay Aggarwal, Aparna Garimella, Balaji Vasan Srinivasan, Anandhavelu N, and Rajiv Jain. 2021. ClauseRec: A Clause Recommendation Framework for AI-aided Contract Authoring. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 8770–8776, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
ClauseRec: A Clause Recommendation Framework for AI-aided Contract Authoring (Aggarwal et al., EMNLP 2021)
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PDF:
https://aclanthology.org/2021.emnlp-main.691.pdf
Video:
 https://aclanthology.org/2021.emnlp-main.691.mp4