Abstract
In this paper we describe an unsupervised WordNet-based Word Sense Disambiguation system, which participated (as UMND1) in the SemEval-2007 Coarsegrained English Lexical Sample task. The system disambiguates a target word by using WordNet-based measures of semantic relatedness to find the sense of the word that is semantically most strongly related to the senses of the words in the context of the target word. We briefly describe this system, the configuration options used for the task, and present some analysis of the results.
| Original language | English (US) |
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| Pages | 390-393 |
| Number of pages | 4 |
| State | Published - 2007 |
| Event | 4th International Workshop on Semantic Evaluations, SemEval 2007 - Prague, Czech Republic Duration: Jun 23 2007 → Jun 24 2007 |
Other
| Other | 4th International Workshop on Semantic Evaluations, SemEval 2007 |
|---|---|
| Country/Territory | Czech Republic |
| City | Prague |
| Period | 6/23/07 → 6/24/07 |
Bibliographical note
Funding Information:This research was partially supported by a National Science Foundation Early CAREER Development award (#0092784).
Publisher Copyright:
© 2007 Association for Computational Linguistics.