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<Paper uid="W04-0821">
  <Title>Meeting of the Association for Computational</Title>
  <Section position="4" start_page="0" end_page="0" type="concl">
    <SectionTitle>
4 Conclusions
</SectionTitle>
    <Paragraph position="0"> Our precision and recall in the SENSEVAL-3 lexical sample tasks was in all cases very close to the median reported by the task organizer, thus demonstrating an ability to obtain credible performance with a simple, robust approach. Additionally, we explored the use of additional features, and we experimented with applying a new unsupervised probabilistic model using human-translated rather than pseudo-translated parallel text, with equivocal results for the various extensions beyond the basic system. In the future we plan to focus our attention more heavily on the learning paradigm and probabilistic modeling, with the particular aim of more effectively exploiting local and document-level context for both sense disambiguation and lexical selection. null</Paragraph>
  </Section>
class="xml-element"></Paper>