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<Paper uid="W04-0820">
  <Title>The upv-unige-CIAOSENSO WSD System</Title>
  <Section position="6" start_page="0" end_page="0" type="concl">
    <SectionTitle>
6 Conclusions and Further Work
</SectionTitle>
    <Paragraph position="0"> The results we obtained in the three tasks of the SENSEVAL-3 we participated in are roughly comparable with those attained in our previous work over the SemCor. In other words, it seems that our system better disambiguate nouns in comparison to words of the others morphological categories.</Paragraph>
    <Paragraph position="1"> A further research direction we plan to investigate is the role of WordNet glosses in the disambiguation, by using the Web as resource to retrieve additional sample sentences, in order to integrate a &amp;quot;leskian&amp;quot; approach within our system. We aim to enhance the performance over verbs, that is the morphological category in which we are facing most difficulty.</Paragraph>
    <Paragraph position="2"> We also took part in the english all-words and english lexical sample tasks in the integrated R2D2-Team system, together with other (un)supervised methods based on Maximum Entropy and Hidden Markov Models, obtaining the following results:  all-words task, scores are both with U and w/o U. LS: Lexical Sample task.</Paragraph>
    <Paragraph position="3"> The integration has been made by means of a voting technique. We plan to improve the integration by assigning a certain weight to each system.</Paragraph>
  </Section>
class="xml-element"></Paper>