Populating legal ontologies using semantic role labeling

This article seeks to address the problem of the ‘resource consumption bottleneck’ of creating legal semantic technologies manually. It describes a semantic role labeling based information extraction system to extract definitions and norms from legislation and represent them as structured norms in l...

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Bibliographic Details
Published in:	Artificial intelligence and law Vol. 29; no. 2; pp. 171 - 211
Main Authors:	Humphreys, Llio, Boella, Guido, van der Torre, Leendert, Robaldo, Livio, Di Caro, Luigi, Ghanavati, Sepideh, Muthuri, Robert
Format:	Journal Article
Language:	English
Published:	Dordrecht Springer Netherlands 01-06-2021 Springer Springer Nature B.V
Subjects:	Artificial Intelligence Computational linguistics Computer Science Document management systems Information retrieval Information Storage and Retrieval Intellectual Property Intellectual property law IT Law Knowledge representation Labeling Language processing Laws, regulations and rules Legal Aspects of Computing Legislation Media Law Natural language interfaces Norms Ontology Original Research Philosophy of Law Semantics Law Ontology Classification Normative reasoning Information extraction Semantic role labeling Artificial intelligence
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Summary:	This article seeks to address the problem of the ‘resource consumption bottleneck’ of creating legal semantic technologies manually. It describes a semantic role labeling based information extraction system to extract definitions and norms from legislation and represent them as structured norms in legal ontologies. The output is intended to help make laws more accessible, understandable, and searchable in a legal document management system.
ISSN:	0924-8463 1572-8382
DOI:	10.1007/s10506-020-09271-3