Description: This paper introduces SenseLearner - a minimally supervised sense tagger that attempts to disambiguate all content words in a text using the sense from WordNet. SenseLearner participated in the SENSEVAL-3 English all words task, and achieved an average accuracy of 64.6%.
Creator: Mihalcea, Rada, 1974- & Faruque, Ehsanul
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Partner: UNT College of Engineering