Abstract
We refine the most frequent sense baseline for word sense disambiguation using a number of novel word sense disambiguation techniques. Evaluating on the Senseval-3 English all words task, our combined system focuses on improving every stage of word sense disambiguation: starting with the lemmatization and part of speech tags used, through the accuracy of the most frequent sense baseline, to highly targeted individual systems. Our supervised systems include a ranking algorithm and a Wikipedia similarity measure.
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CITATION STYLE
Preiss, J., Dehdari, J., King, J., & Mehay, D. (2009). Refining the most frequent sense baseline. In SEW 2009 - Semantic Evaluations: Recent Achievements and Future Directions at the 2009 North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2009 - Proceedings (pp. 10–18). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1621969.1621973
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