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Towards Construction of Legal Ontology for Korean Legislation

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conference contribution
posted on 18.11.2020, 00:56 by Thi Thuy Phan, Ho-Pun Lam, Mustafa Hashmi, Yongsun Choi
Automating information extraction from legal documents and formalising them into a machine understandable
format has long been an integral challenge to legal reasoning. Most approaches in the past consist of highly
complex solutions that use annotated syntactic structures and grammar to distil rules. The current research
trend is to utilise state-of-the-art natural language processing (NLP) approaches to automate these tasks, with minimum human interference. In this paper, based on its functional aspects, we propose a legal taxonomy of
semantic types in Korean legislation, such as definitional provision, deeming provision, penalty, obligation,
permission, prohibition, etc. In addition to this, a NLP classifier has been developed to facilitate the automated
legal norms classification process and an overall F1 score of 0.97 has been achieved.

History

Publication Date

04/11/2020

Proceedings

Proceedings of The 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (KEOD 2020)

Publisher

ScitePress

Place of publication

Setúbal, Portugal

Name of conference

The 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (KEOD 2020)

Location

Setubal, Portugal

Starting Date

02/11/2020

Finshing Date

04/11/2020

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