Semantic Web Dog Food

Presented at: The Sixth International Language Resources and Evaluation Conference (LREC2008)

by Bartosz Broda, Magdalena Derwojedowa, Maciej Piasecki, Stanislaw Szpakowicz

The construction of a wordnet, a labour-intensive enterprise, can be significantly assisted by automatic grouping of lexical material and discovery of lexical semantic relations. The objective is to ensure high quality of automatically acquired results before they are presented for lexicographers approval. We discuss a software tool that suggests synset members using a measure of semantic relatedness with a given verb or adjective; this extends previous work on nominal synsets in Polish WordNet. Syntactically-motivated constraints are deployed on a large morphologically annotated corpus of Polish. Evaluation has been performed via the WordNet-Based Similarity Test and additionally supported by human raters. A lexicographer also manually assessed a suitable sample of suggestions. The results compare favourably with other known methods of acquiring semantic relations.

Keywords: LR national/international projects, organizational/policy issues, Lexicon, lexical database, Statistical methods, Linguistics

Resource URI on the dog food server: http://data.semanticweb.org/conference/lrec/2008/papers/459

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