It has been widely assumed that sense distinctions in WordNet are often too fine-grained for applications such as Machine Translation, Information Retrieval, Text Classification, Document clustering, Question Answering, etc. This has led to a number of studies in sense clustering, i.e., collapsing sense distinctions in WordNet that can be ignored for most practical applications [1,5,6]. At the ...