Paper: Aligning Features With Sense Distinction Dimensions

ACL ID P06-2118
Title Aligning Features With Sense Distinction Dimensions
Venue Annual Meeting of the Association of Computational Linguistics
Session Poster Session
Year 2006
Authors

In this paper we present word sense disambiguation (WSD) experiments on ten highly polysemous verbs in Chinese, where significant performance improvements are achieved using rich linguistic features. Our system performs significantly better, and in some cases substantially better, than the baseline on all ten verbs. Our results also demonstrate that features extracted from the output of an automatic Chinese semantic role labeling system in general benefited the WSD system, even though the amount of improvement was not consistent across the verbs. For a few verbs, semantic role information actually hurt WSD performance. The inconsistency of feature performance is a general characteristic of the WSD task, as has been observed by others. We argue that this result can be explained by the fact ...