SenseLearner: Minimally Supervised Word Sense Disambiguation for All Words in Open Text
Rada F. Mihalcea, Ehsanul Faruque · University of North Texas Digital Library (University of North Texas) · 2004
This paper introduces SENSELEARNER – a minimally supervised sense tagger that attempts to disambiguate all content words in a text using the senses from WordNet. SENSELEARNER participated in the SENSEVAL-3 English all words task, and achieved an average accuracy of 64.6%. 1