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Automatic extraction of semantic relationships for WordNet by means of pattern learning from Wikipedia

Author
Ruiz-Casado, María; Alfonseca Cubero, Enrique; Castells Azpilicueta, Pablountranslated
Entity
UAM. Departamento de Ingeniería Informática
Publisher
Springer-Verlag Berlin Heidelberg
Date
2005
Citation
10.1007/11428817_7
Natural Language Processing and Information Systems: 10th International Conference on Applications of Natural Language to Information Systems, NLDB 2005, Alicante, Spain, June 15-17, 2005. Proceedings. Lecture Notes in Computer Science, Volumen 3513. Springer 2005. 67-79.
 
 
 
ISSN
0302-9743 (print); 1611-3349 (online)
ISBN
978-3-540-26031-8 (print); 978-3-540-32110-1 (online)
DOI
10.1007/11428817_7
Funded by
This work has been sponsored by CICYT, project number TIC2002-01948.
Editor's Version
http://dx.doi.org/10.1007/11428817_7
Subjects
Database Management; Computer Communication Networks; Logics and Meanings of Programs; Information Storage and Retrieval; Artificial Intelligence; Mathematical Logic; Formal Languages; Informática
URI
http://hdl.handle.net/10486/664305
Note
The final publication is available at Springer via http://dx.doi.org/10.1007/11428817_7
Proceedings of 10th International Conference on Applications of Natural Language to Information Systems, NLDB 2005, Alicante, Spain, June 15-17, 2005.
Rights
© Springer-Verlag Berlin Heidelberg 2005

Abstract

This paper describes an automatic approach to identify lexical patterns which represent semantic relationships between concepts, from 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 1200 new relationships that did not appear in WordNet originally. The precision of these relationships ranges between 0.61 and 0.69, depending on the relation.
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  • Producción científica en acceso abierto de la UAM [14730]

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