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EMNLP
2008

Word Sense Disambiguation Using OntoNotes: An Empirical Study

10 years 2 months ago
Word Sense Disambiguation Using OntoNotes: An Empirical Study
The accuracy of current word sense disambiguation (WSD) systems is affected by the fine-grained sense inventory of WordNet as well as a lack of training examples. Using the WSD examples provided through OntoNotes, we conduct the first large-scale WSD evaluation involving hundreds of word types and tens of thousands of sense-tagged examples, while adopting a coarse-grained sense inventory. We show that though WSD systems trained with a large number of examples can obtain a high level of accuracy, they nevertheless suffer a substantial drop in accuracy when applied to a different domain. To address this issue, we propose combining a domain adaptation technique using feature augmentation with active learning. Our results show that this approach is effective in reducing the annotation effort required to adapt a WSD system to a new domain. Finally, we propose that one can maximize the dual benefits of reducing the annotation effort while ensuring an increase in WSD accuracy, by only perfor...
Zhi Zhong, Hwee Tou Ng, Yee Seng Chan
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where EMNLP
Authors Zhi Zhong, Hwee Tou Ng, Yee Seng Chan
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