2026-05-18T07:05:30Zhttps://iris.cnr.it/oai/requestoai:iris.cnr.it:20.500.14243/1348152024-03-04T01:05:08Zcom_20.500.14243_29com_20.500.14243_21col_20.500.14243_30ou_ou239
Ontology learning from Italian legal texts
Lenci A
Montemagni S
Pirrelli V
Giulia V
Joost Breuker
Pompeu Casanova
Michel C.A. Klein
Enrico Francesconi
Lenci A.
Montemagni S.
Pirrelli V.
Giulia V.
Ontology Learning
document management
legal knowledge extraction
The paper reports on the methodology and preliminary results of a case study in automatically extracting ontological knowledge from Italian legislative texts. We use a fully-implemented ontology learning system (T2K) that includes a battery of tools for Natural Language Processing (NLP), statistical text analysis and machine language learning. Tools are dynamically integrated to provide an incremental representation of the content of vast repositories of unstructured documents. Evaluated results, however preliminary, show the great potential of NLP-powered incremental systems like T2K for accurate large-scale semi-automatic extraction of legal ontologies.
2009
info:eu-repo/semantics/bookPart
https://hdl.handle.net/20.500.14243/134815
10.3233/978-1-58603-942-4-75
info:eu-repo/semantics/altIdentifier/isbn/978-1-58603-942-4
eng
ispartofbook:Law, Ontologies and the Semantic Web - Channelling the Legal Information Flood
firstpage:75
lastpage:94
numberofpages:20
alleditors:Joost Breuker; Pompeu Casanovas; Michel C.A. Klein; Enrico Francesconi