Paper: Word Sense Disambiguation Using Sense Examples Automatically Acquired From A Second Language

ACL ID H05-1069
Title Word Sense Disambiguation Using Sense Examples Automatically Acquired From A Second Language
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2005
Authors

We present a novel almost-unsupervised approach to the task of Word Sense Dis- ambiguation (WSD). We build sense ex- amples automatically, using large quanti- ties of Chinese text, and English-Chinese and Chinese-English bilingual dictionar- ies, taking advantage of the observation that mappings between words and mean- ings are often different in typologically distant languages. We train a classifier on the sense examples and test it on a gold standard English WSD dataset. The eval- uation gives results that exceed previous state-of-the-art results for comparable sys- tems. We also demonstrate that a little manual effort can improve the quality of sense examples, as measured by WSD ac- curacy. The performance of the classifier on WSD also improves as the number of training sense examples i...