Integrating Multiple Knowledge Sources to Disambiguate Word Sense: An Exemplar-Based Approach
| dc.creator | Ng, Hwee Tou | |
| dc.creator | Lee, Hian Beng | |
| dc.date | 1996-06-29 | |
| dc.date.accessioned | 2026-07-07T09:10:26Z | |
| dc.date.available | 2026-07-07T09:10:26Z | |
| dc.description | In this paper, we present a new approach for word sense disambiguation (WSD) using an exemplar-based learning algorithm. This approach integrates a diverse set of knowledge sources to disambiguate word sense, including part of speech of neighboring words, morphological form, the unordered set of surrounding words, local collocations, and verb-object syntactic relation. We tested our WSD program, named {\sc Lexas}, on both a common data set used in previous work, as well as on a large sense-tagged corpus that we separately constructed. {\sc Lexas} achieves a higher accuracy on the common data set, and performs better than the most frequent heuristic on the highly ambiguous words in the large corpus tagged with the refined senses of {\sc WordNet}. | |
| dc.description | In Proceedings of ACL96, 8 pages | |
| dc.identifier | https://arxiv.org/abs/cmp-lg/9606032 | |
| dc.identifier | http://arxiv.org/abs/cmp-lg/9606032 | |
| dc.identifier | ACL-96 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/151351 | |
| dc.subject | Computation and Language | |
| dc.title | Integrating Multiple Knowledge Sources to Disambiguate Word Sense: An Exemplar-Based Approach | |
| dc.type | text |