Paper: Two Graph-Based Algorithms For State-Of-The-Art WSD

ACL ID W06-1669
Title Two Graph-Based Algorithms For State-Of-The-Art WSD
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2006

This paper explores the use of two graph algorithms for unsupervised induction and tagging of nominal word senses based on corpora. Our main contribution is the op- timization of the free parameters of those algorithms and its evaluation against pub- licly available gold standards. We present a thorough evaluation comprising super- vised and unsupervised modes, and both lexical-sample and all-words tasks. The results show that, in spite of the infor- mation loss inherent to mapping the in- duced senses to the gold-standard, the optimization of parameters based on a small sample of nouns carries over to all nouns, performing close to supervised sys- tems in the lexical sample task and yield- ing the second-best WSD systems for the Senseval-3 all-words task.