Applying cross-lingual WSD to wordnet development

Abstract

The automatic development of semantic resources constitutes an important challenge in the NLP community. The methods used generally exploit existing large-scale resources, such as Princeton WordNet, often combined with information extracted from multilingual resources and parallel corpora. In this paper we show how Cross-Lingual Word Sense Disambiguation can be applied to wordnet development. We apply the proposed method to WOLF, a free wordnet for French still under construction, in order to fill synsets that did not contain any literal yet and increase its coverage.

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