Clustering-based Automatic Construction of Legal Entity Knowledge Base from Contracts

• URL: http://arxiv.org/abs/2012.01942v2
• Date: Mon, 7 Dec 2020 09:49:26 GMT
• Title: Clustering-based Automatic Construction of Legal Entity Knowledge Base from Contracts
• Authors: Fuqi Song and \'Eric de la Clergerie
• Abstract summary: We propose a clustering-based approach to automatically generate a reliable knowledge base of legal entities from given contracts. The proposed method is robust to different types of errors brought by pre-processing such as OCR and NER. Compared to the collected ground-truth data, our method is able to recall 84% of the knowledge.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: In contract analysis and contract automation, a knowledge base (KB) of legal entities is fundamental for performing tasks such as contract verification, contract generation and contract analytic. However, such a KB does not always exist nor can be produced in a short time. In this paper, we propose a clustering-based approach to automatically generate a reliable knowledge base of legal entities from given contracts without any supplemental references. The proposed method is robust to different types of errors brought by pre-processing such as Optical Character Recognition (OCR) and Named Entity Recognition (NER), as well as editing errors such as typos. We evaluate our method on a dataset that consists of 800 real contracts with various qualities from 15 clients. Compared to the collected ground-truth data, our method is able to recall 84\% of the knowledge.

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