Coarse Word-Sense Disambiguation Using Common Sense

Coarse word sense disambiguation (WSD) is an NLP task that is both important and practical: it aims to distinguish senses of a word that have very different meanings, while avoiding the complexity that comes from trying to finely distinguish every possible word sense. Reasoning techniques that make use of common sense information can help to solve the WSD problem by taking word meaning and context into account. We have created a system for coarse word sense disambiguation using blending, a common sense reasoning technique, to combine information from SemCor, WordNet, ConceptNet and Extended WordNet. Within that space, a correct sense is suggested based on the similarity of the ambiguous word to each of its possible word senses. The general blending-based system performed well at the task, achieving an f-score of 80.8\% on the 2007 SemEval Coarse Word Sense Disambiguation task.