Paper: It Makes Sense: A Wide-Coverage Word Sense Disambiguation System for Free Text

ACL ID P10-4014
Title It Makes Sense: A Wide-Coverage Word Sense Disambiguation System for Free Text
Venue Annual Meeting of the Association of Computational Linguistics
Session System Demonstration
Year 2010
Authors

Word sense disambiguation (WSD) systems based on supervised learning achieved the best performance in SensE- val and SemEval workshops. However, there are few publicly available open source WSD systems. This limits the use of WSD in other applications, especially for researchers whose research interests are not in WSD. In this paper, we present IMS, a supervised English all-words WSD system. The flex- ible framework of IMS allows users to in- tegrate different preprocessing tools, ad- ditional features, and different classifiers. By default, we use linear support vector machines as the classifier with multiple knowledge-based features. In our imple- mentation, IMS achieves state-of-the-art results on several SensEval and SemEval tasks.