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<Paper uid="W04-0838">
  <Title>SenseLearner: Minimally Supervised Word Sense Disambiguation for All Words in Open Text</Title>
  <Section position="7" start_page="0" end_page="0" type="concl">
    <SectionTitle>
5 Conclusion
</SectionTitle>
    <Paragraph position="0"> In this paper, we proposed and evaluated a new algorithm for minimally supervised word-sense disambiguation that attempts to disambiguate all content words in a text using the senses from Word-Net. The algorithm was implemented in a system called SENSELEARNER, which participated in the SENSEVAL-3 English all words task and obtained an average accuracy of 64.6% - a significant improvement over the most frequent sense baseline of 60.9%.</Paragraph>
  </Section>
class="xml-element"></Paper>