A Proposal for word sense disambiguation using conceptual distance

This paper presents a method for the resolution of lexical ambiguity and its automatic evaluation over the Brown Corpus. The method relies on the use of the wide-coverage noun taxonomy of WordNet and the notion of conceptual distance among concepts, captured by a Conceptual Density formula developed...

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Detalles Bibliográficos
Autores: Agirre, Eneko, Rigau Claramunt, German
Tipo de recurso: informe técnico
Fecha de publicación:1996
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/82606
Acceso en línea:https://hdl.handle.net/2117/82606
Access Level:acceso abierto
Palabra clave:Word sense disambiguation
Conceptual distance
WordNet
SemCor
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
Descripción
Sumario:This paper presents a method for the resolution of lexical ambiguity and its automatic evaluation over the Brown Corpus. The method relies on the use of the wide-coverage noun taxonomy of WordNet and the notion of conceptual distance among concepts, captured by a Conceptual Density formula developed for this purpose. This fully automatic method requires no hand coding of lexical entries, hand tagging of text nor any kind of training process. The results of the experiment have been automatically evaluated against SemCor, the sense-tagged version of the Brown Corpus.