Assessing the contribution of shallow and deep knowledge sources for word sense disambiguation.
Corpus-based techniques have proved to be very beneficial in the development of efficient and accurate approaches to word sense disambiguation (WSD) despite the fact that they generally represent relatively shallow knowledge. It has always been thought, however, that WSD could also benefit from deep...
| Publicado en: | Language Resources & Evaluation Vol. 44; no. 4; pp. 295 - 314 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Springer Nature
Dec2010
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=65198913&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 65198913 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Dec2010 vid: 44 iid: 4 pid: 237 pub: Springer Nature artinfo: ui: 65198913 10.1007/s10579-009-9107-y ppf: 295 ppct: 19 formats: fmt: @attributes: type: P size: 295KB tig: atl: Assessing the contribution of shallow and deep knowledge sources for word sense disambiguation. aug: au: Specia, Lucia Stevenson, Mark das Graças Volpe Nunes, Maria affil: Research Institute for Information and Language Processing, University of Wolverhampton, Stafford Street Wolverhampton WV1 1SB UK Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello Sheffield S1 4DP UK Universidade de São Paulo, Caixa Postal 668 São Carlos 13560-970 Brazil su: Vocabulary Language & languages Theory of knowledge Computer programming English language sug: subj: Vocabulary Language & languages Theory of knowledge Computer programming English language keyword: Inductive logic programming Knowledge sources Word sense disambiguation ab: Corpus-based techniques have proved to be very beneficial in the development of efficient and accurate approaches to word sense disambiguation (WSD) despite the fact that they generally represent relatively shallow knowledge. It has always been thought, however, that WSD could also benefit from deeper knowledge sources. We describe a novel approach to WSD using inductive logic programming to learn theories from first-order logic representations that allows corpus-based evidence to be combined with any kind of background knowledge. This approach has been shown to be effective over several disambiguation tasks using a combination of deep and shallow knowledge sources. Is it important to understand the contribution of the various knowledge sources used in such a system. This paper investigates the contribution of nine knowledge sources to the performance of the disambiguation models produced for the SemEval-2007 English lexical sample task. The outcome of this analysis will assist future work on WSD in concentrating on the most useful knowledge sources. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2010. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2010 holdings: @attributes: islocal: N |
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