The paper focuses on the automatic extraction of domain knowledge from Italian legal texts and presents a fully-implemented ontology learning system (T2K, Text-2-Knowledge) that includes a battery of tools for Natural Language Processing, statistical text analysis and machine learning. Evaluated results show the considerable potential of systems like T2K, exploiting an incremental interleaving of NLP and machine learning techniques for accurate large-scale semi-automatic extraction and structuring of domain-specific knowledge.

Dal testo alla conoscenza e ritorno: estrazione terminologica e annotazione semantica di basi documentali di dominio.

Dell'Orletta Felice;Marchi Simone;Montemagni Simonetta;Pirrelli Vito;Venturi Giulia
2008

Abstract

The paper focuses on the automatic extraction of domain knowledge from Italian legal texts and presents a fully-implemented ontology learning system (T2K, Text-2-Knowledge) that includes a battery of tools for Natural Language Processing, statistical text analysis and machine learning. Evaluated results show the considerable potential of systems like T2K, exploiting an incremental interleaving of NLP and machine learning techniques for accurate large-scale semi-automatic extraction and structuring of domain-specific knowledge.
2008
Istituto di linguistica computazionale "Antonio Zampolli" - ILC
Italiano
Terminologia analisi testuale e documentazione nella città digitale
Atti del Convegno Nazionale Ass.I.Term
Anno 26, numero 1-2
197
218
22
http://www.assiterm91.it/wp-content/uploads/2010/11/Convegno-2008.pdf
5-7/06/2008
Arcavacata di Rende (CS)
Natural Language Processing
Machine Learning
Knowledge extraction from texts
Ontology learning
Legal ontologies
6
none
Dell'Orletta, Felice; Lenci, Alessando; Marchi, Simone; Montemagni, Simonetta; Pirrelli, Vito; Venturi, Giulia
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/65083
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