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<Paper uid="C04-1173">
  <Title>Word Sense Disambiguation using a dictionary for sense similarity measure</Title>
  <Section position="7" start_page="0" end_page="0" type="concl">
    <SectionTitle>
8 Conclusion
</SectionTitle>
    <Paragraph position="0"> We have presented here an algorithm giving a measure of lexical similarity, built from information found in a dictionary. This has been used to disambiguate dictionary entries, with a method that needs no other source of information (except part-of-speech tagging), no annotated data. The coverage of the method depends only on the lexical coverage of the dictionary used. It seems to give promising results on disambiguating nouns, using only nouns or nouns and verbs. We intend to try the method after enriching the network of senses with adjectives and/or adverbs. We also intend, of course, to try the method on disambiguating verbs and adjectives. null Moreover, the method can be rather straight-forwardly extended to any type of disambiguation by considering a context with a target word as a node added in the graph of senses (a kind of virtual definition). We have not tested this idea yet. Since our method gives a ranked list of sense candidates, we also consider using finer performance measures, taking into account confidence degrees, as proposed in (Resnik and Yarowsky, 2000).</Paragraph>
  </Section>
class="xml-element"></Paper>