This paper describes the automatic transformation of a Generative Lexicon (GL) based Ontology into OWL, the Semantic Web ontology language. Furthermore, the OWL ontology is automatically enriched by means of a bottom-up procedure that extracts additional semantic information (relationships, features, predicates and quantifier restrictions) from the lexicon. The contribution of this research is two-fold. On one hand, we introduce a methodology for the formalisation of GL ontologies. On the other, we have developed automatic procedures that bring out a formalised, reasoning-capable, and semantically rich ontology, thus suitable for Natural Language Processing semantic tasks.

Automatically converting and enriching a computational lexicon Ontology for NLP semantic tasks

Monachini M;
2007

Abstract

This paper describes the automatic transformation of a Generative Lexicon (GL) based Ontology into OWL, the Semantic Web ontology language. Furthermore, the OWL ontology is automatically enriched by means of a bottom-up procedure that extracts additional semantic information (relationships, features, predicates and quantifier restrictions) from the lexicon. The contribution of this research is two-fold. On one hand, we introduce a methodology for the formalisation of GL ontologies. On the other, we have developed automatic procedures that bring out a formalised, reasoning-capable, and semantically rich ontology, thus suitable for Natural Language Processing semantic tasks.
Campo DC Valore Lingua
dc.authority.orgunit Istituto di linguistica computazionale "Antonio Zampolli" - ILC -
dc.authority.people Toral A it
dc.authority.people Monachini M it
dc.authority.people Muñoz R it
dc.collection.id.s 71c7200a-7c5f-4e83-8d57-d3d2ba88f40d *
dc.collection.name 04.01 Contributo in Atti di convegno *
dc.contributor.appartenenza Istituto di linguistica computazionale "Antonio Zampolli" - ILC *
dc.contributor.appartenenza.mi 918 *
dc.date.accessioned 2024/02/19 19:34:23 -
dc.date.available 2024/02/19 19:34:23 -
dc.date.issued 2007 -
dc.description.abstract This paper describes the automatic transformation of a Generative Lexicon (GL) based Ontology into OWL, the Semantic Web ontology language. Furthermore, the OWL ontology is automatically enriched by means of a bottom-up procedure that extracts additional semantic information (relationships, features, predicates and quantifier restrictions) from the lexicon. The contribution of this research is two-fold. On one hand, we introduce a methodology for the formalisation of GL ontologies. On the other, we have developed automatic procedures that bring out a formalised, reasoning-capable, and semantically rich ontology, thus suitable for Natural Language Processing semantic tasks. -
dc.description.affiliations Istituto di linguistica computazionale "Antonio Zampolli" -
dc.description.allpeople Toral, A; Monachini, M; Muñoz, R -
dc.description.allpeopleoriginal Toral A.; Monachini M.; Muñoz R -
dc.description.fulltext none en
dc.description.numberofauthors 3 -
dc.identifier.isbn 978-83-7177-413-3 -
dc.identifier.uri https://hdl.handle.net/20.500.14243/65064 -
dc.language.iso eng -
dc.publisher.country POL -
dc.publisher.name Fundacja Uniwersytetu im A. Mickiewicza -
dc.publisher.place Poznan -
dc.relation.conferencedate 5-7 Ottobre 2007 -
dc.relation.conferencename LTC07 - 3rd Language & Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics -
dc.relation.conferenceplace Poznan -
dc.relation.firstpage 216 -
dc.relation.lastpage 220 -
dc.title Automatically converting and enriching a computational lexicon Ontology for NLP semantic tasks en
dc.type.driver info:eu-repo/semantics/conferenceObject -
dc.type.full 04 Contributo in convegno::04.01 Contributo in Atti di convegno it
dc.type.miur 273 -
dc.type.referee Sì, ma tipo non specificato -
dc.ugov.descaux1 84686 -
iris.orcid.lastModifiedDate 2024/04/04 18:43:47 *
iris.orcid.lastModifiedMillisecond 1712249027689 *
iris.sitodocente.maxattempts 1 -
Appare nelle tipologie: 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/20.500.14243/65064
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