In word sense disambiguation, choosing the most frequent sense for an ambiguous word is a powerful heuristic. However, its usefulness is restricted by the availability of sense-an...
It is popular in WSD to use contextual information in training sense tagged data. Co-occurring words within a limited window-sized context support one sense among the semantically...
Supervised approaches to Word Sense Disambiguation (WSD) have been shown to outperform other approaches but are hampered by reliance on labeled training examples (the data acquisi...
Word Sense Disambiguation (WSD), in the field of Natural Language Processing (NLP), consists in assigning the correct sense (semantics) to a word form (lexeme) by means of the cont...
Davide Buscaldi, Giovanna Guerrini, Marco Mesiti, ...