Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/40533
DC Field | Value | |
---|---|---|
dc.title | Scaling up word sense disambiguation via parallel texts | |
dc.contributor.author | Chan, Y.S. | |
dc.contributor.author | Ng, H.T. | |
dc.date.accessioned | 2013-07-04T08:06:31Z | |
dc.date.available | 2013-07-04T08:06:31Z | |
dc.date.issued | 2005 | |
dc.identifier.citation | Chan, Y.S., Ng, H.T. (2005). Scaling up word sense disambiguation via parallel texts. Proceedings of the National Conference on Artificial Intelligence 3 : 1037-1042. ScholarBank@NUS Repository. | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/40533 | |
dc.description.abstract | A critical problem faced by current supervised WSD systems is the lack of manually annotated training data. Tackling this data acquisition bottleneck is crucial, in order to build high-accuracy and wide-coverage WSD systems. In this paper, we show that the approach of automatically gathering training examples from parallel texts is scalable to a large set of nouns. We conducted evaluation on the nouns of SENSEVAL-2 English all-words task, using fine-grained sense scoring. Our evaluation shows that training on examples gathered from 680MB of parallel texts achieves accuracy comparable to the best system of SENSEVAL-2 English all-words task, and significantly outperforms the baseline of always choosing sense 1 of WordNet. Copyright © 2005, American Association for Artificial Intelligence (www.aaai.org). All rights reserved. | |
dc.source | Scopus | |
dc.type | Conference Paper | |
dc.contributor.department | COMPUTATIONAL SCIENCE | |
dc.description.sourcetitle | Proceedings of the National Conference on Artificial Intelligence | |
dc.description.volume | 3 | |
dc.description.page | 1037-1042 | |
dc.description.coden | PNAIE | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
Show simple item record
Files in This Item:
There are no files associated with this item.
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.