Towards Robust High Performance Word Sense Disambiguation of English Verbs Using Rich Linguistic Features

This paper shows that our WSD system using rich linguistic features achieved high accuracy in the classification of English SENSEVAL2 verbs for both fine-grained (64.6%) and coarse-grained (73.7%) senses. We describe three specific enhancements to our treatment of rich linguistic features and present their separate and combined contributions to our system's performance. Further experiments showed that our system had robust performance on test data without high quality rich features.

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