Taming Sense Sparsity: a Common-Sense Approach
نویسندگان
چکیده
English. We present a novel algorithm and a linguistic resource named CLOSEST after ‘Common SEnse STrainer’. The resource contains a list of the main senses associated to a given term, and it was obtained by applying a simple set of pruning heuristics to the senses provided in the NASARI vectors for the set of 15K most frequent English terms. The preliminary experimentation provided encouraging results. Italiano. In questo lavoro presentiamo un algoritmo e una risorsa linguistica, ClOSeSt, che contiene i sensi più rilevanti per i 15K termini più frequenti del dizionario inglese. L’algoritmo implementato utilizza una risorsa esistente che codifica conoscenza di tipo enciclopedico, e poggia sulla nozione di senso comune per filtrare i possibili sensi associati a ciascun termine. La valutazione preliminare ha fornito risultati incoraggianti in merito alla qualità dei sensi estratti.
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