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<Paper uid="P06-2037">
  <Title>Low-cost Enrichment of Spanish WordNet with Automatically Translated Glosses: Combining General and Specialized Models</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper studies the enrichment of Spanish WordNet with synset glosses automatically obtained from the English Word-Net glosses using a phrase-based Statistical Machine Translation system. We construct the English-Spanish translation system from a parallel corpus of proceedings of the European Parliament, and study how to adapt statistical models to the domain of dictionary definitions. We build specialized language and translation models from a small set of parallel definitions and experiment with robust manners to combine them. A statistically significant increase in performance is obtained. The best system is finally used to generate a definition for all Spanish synsets, which are currently ready for a manual revision.</Paragraph>
    <Paragraph position="1"> As a complementary issue, we analyze the impact of the amount of in-domain data needed to improve a system trained entirely on out-of-domain data.</Paragraph>
  </Section>
class="xml-element"></Paper>