TreeMatch: A fully unsupervised WSD system using dependency knowledge on a specific domain

Authors:
Andrew Tran;Chris Bowes;David Brown;Ping Chen;Max Choly;Wei Ding
Affiliations:
University of Houston-Downtown;University of Houston-Downtown;University of Houston-Downtown;University of Houston-Downtown;University of Massachusetts-Boston;University of Massachusetts-Boston
Venue:
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Year:
2010

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Abstract

Word sense disambiguation (WSD) is one of the main challenges in Computational Linguistics. TreeMatch is a WSD system originally developed using data from SemEval 2007 Task 7 (Coarse-grained English All-words Task) that has been adapted for use in SemEval 2010 Task 17 (All-words Word Sense Disambiguation on a Specific Domain). The system is based on a fully unsupervised method using dependency knowledge drawn from a domain specific knowledge base that was built for this task. When evaluated on the task, the system precision performs above the First Sense Baseline.