Paper: Word Sense Disambiguation Incorporating Lexical and Structural Semantic Information

ACL ID D07-1050
Title Word Sense Disambiguation Incorporating Lexical and Structural Semantic Information
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2007
Authors

We present results that show that incorporat- ing lexical and structural semantic informa- tion is effective for word sense disambigua- tion. We evaluated the method by using pre- cise information from a large treebank and an ontology automatically created from dic- tionary sentences. Exploiting rich semantic and structural information improves preci- sion 2–3%. The most gains are seen with verbs, with an improvement of 5.7% over a model using only bag of words and n-gram features.