Authors
Stephen Tratz, Antonio Sanfilippo, Michelle Gregory, Alan Chappell, Christian Posse, Paul Whitney
Publication date
2007/6
Conference
Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007)
Pages
264-267
Description
In this paper, we described the PNNL Word Sense Disambiguation system as applied to the English all-word task in SemEval 2007. We use a supervised learning approach, employing a large number of features and using Information Gain for dimension reduction. The rich feature set combined with a Maximum Entropy classifier produces results that are significantly better than baseline and are the highest F-score for the fined-grained English allwords subtask of SemEval.
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S Tratz, A Sanfilippo, M Gregory, A Chappell, C Posse… - Proceedings of the Fourth International Workshop on …, 2007