Automatic Domain Assignment for Word Sense Alignment

Tommaso Caselli, Carlo Strapparava

Abstract: This paper reports on the development of a hybrid and simple method based on a machine learning classifier (Naive Bayes), Word Sense Disambiguation and rules, for the automatic assignment of WordNet Domains to nominal entries of a lexicographic dictionary, the Senso Comune De Mauro Lexicon. The system obtained an F1 score of 0.58, with a Precision of 0.70. We further used the automatically assigned domains to filter out word sense alignments between MultiWordNet and Senso Comune. This has led to an improvement in the quality of the sense alignments showing the validity of the approach for domain assignment and the importance of domain information for achieving good sense alignments.