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.

Populating legal ontologies using semantic role labeling

Humphreys L.
;
Boella G.;Robaldo L.;Di Caro L.;
2020-01-01

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.
forthcoming
1
20
Artificial intelligence; Classification; Information extraction; Law; Normative reasoning; Ontology; Semantic role labeling
Humphreys L.; Boella G.; van der Torre L.; Robaldo L.; Di Caro L.; Ghanavati S.; Muthuri R.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1762571
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