Semi-automatic knowledge population in a legal document management system

Every organization has to deal with operational risks, arising from the execution of a company’s primary business functions. In this paper, we describe a legal knowledge management system which helps users understand the meaning of legislative text and the relationship between norms. While much of t...

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Bibliographic Details
Published in:Artificial intelligence and law 2019-06, Vol.27 (2), p.227-251
Main Authors: Boella, Guido, Di Caro, Luigi, Leone, Valentina
Format: Article
Language:English
Subjects:
Artificial Intelligence
Automation
Business law
Computer Science
Document management systems
Information Storage and Retrieval
Intellectual Property
IT Law
Knowledge management
Legal Aspects of Computing
Media Law
Natural language processing
Norms
Philosophy of Law
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Summary:Every organization has to deal with operational risks, arising from the execution of a company’s primary business functions. In this paper, we describe a legal knowledge management system which helps users understand the meaning of legislative text and the relationship between norms. While much of the knowledge requires the input of legal experts, we focus in this article on NLP applications that semi-automate essential time-consuming and lower-skill tasks—classifying legal documents, identifying cross-references and legislative amendments, linking legal terms to the most relevant definitions, and extracting key elements of legal provisions to facilitate clarity and advanced search options. The use of Natural Language Processing tools to semi-automate such tasks makes the proposal a realistic commercial prospect as it helps keep costs down while allowing greater coverage.
ISSN:0924-8463
1572-8382
DOI:10.1007/s10506-018-9239-8