Article (Scientific journals)
Populating legal ontologies using semantic role labeling
Humpreys, Lilo; Boella, Guido; van der Torre, Leon et al.
2021In Artificial Intelligence and Law, 29 (2), p. 171-211
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Keywords :
Semantic role labeling; Legal ontology; Legaltech
Abstract :
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.
Disciplines :
Computer science
Author, co-author :
Humpreys, Lilo
Boella, Guido
van der Torre, Leon ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Robaldo, Livio 
Di Caro, Luigi
Ghanavati, Sepideh
Muthuri, Robert
External co-authors :
yes
Language :
English
Title :
Populating legal ontologies using semantic role labeling
Publication date :
2021
Journal title :
Artificial Intelligence and Law
ISSN :
1572-8382
Publisher :
Kluwer Academic Publishers, Netherlands
Volume :
29
Issue :
2
Pages :
171-211
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Computational Sciences
Available on ORBilu :
since 22 January 2022

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