The algorithm proved effective at Senseval-3 (Mihalcea and Edmonds, 2004) and, nowadays, it still represents the state-of-the-art in WSD (Pradhan et al., 2007).
they addressed these issues: (i) independently modeling domain and syntagmatic aspects of sense distinction to improve feature representativeness; and (ii) exploiting external knowledge acquired from unlabeled data, with the purpose of drastically reducing the amount of labeled training data.