Building WordNets by machine translation of sense tagged corpora

Abstract

This paper describes a methodology for the construction of WordNets based on machine translation of an English sense tagged corpus. For the construction of such a corpus we used two freely available resources: the Semcor Corpus and the Princeton WordNet Gloss Corpus. This methodology is applied on the construction of Spanish and Catalan WordNet 3.0. In our first experiments we used a simple word alignment algorithm obtaining precision results comparable to those obtained by methods based on bilingual dictionaries. After that, we used a freely available statistical word alignment algorithm (Berkeley Aligner) obtaining better results. This methodology can be suitable for those languages with an available statistical machine translation system and can be used for either constructing WordNets from the scratch or for enlarging existing WordNets.