Automatising the learning of lexical patterns: An application to the enrichment of WordNet by extracting semantic relationships from Wikipedia
EntityUAM. Departamento de Ingeniería Informática
10.1016/j.datak.2006.06.011Data & Knowledge Engineering 61.3 (2007): 484 – 499
ISSN0169-023X (print); 1872-6933 (online)
Funded byThis work has been sponsored by MEC, project number TIN-2005-06885
SubjectsInformation extraction; Lexical patterns; Ontology and thesaurus acquisition; Relation extraction; Informática
NoteThis is the author’s version of a work that was accepted for publication in Journal Data & Knowledge Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal Data & Knowledge Engineering, 61, 3, (2007) DOI: 10.1016/j.datak.2006.06.011
Esta obra está bajo una licencia de Creative Commons Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional.
This paper describes an automatic approach to identify lexical patterns that represent semantic relationships between concepts in an on-line encyclopedia. Next, these patterns can be applied to extend existing ontologies or semantic networks with new relations. The experiments have been performed with the Simple English Wikipedia and WordNet 1.7. A new algorithm has been devised for automatically generalising the lexical patterns found in the encyclopedia entries. We have found general patterns for the hyperonymy, hyponymy, holonymy and meronymy relations and, using them, we have extracted more than 2600 new relationships that did not appear in WordNet originally. The precision of these relationships depends on the degree of generality chosen for the patterns and the type of relation, being around 60-70% for the best combinations proposed.
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