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<Paper uid="C94-2114">
  <Title>A Best-Match Algorithm for Broad-Coverage Example-Based Disambiguation</Title>
  <Section position="7" start_page="720" end_page="720" type="concl">
    <SectionTitle>
6 Conclusion
</SectionTitle>
    <Paragraph position="0"> Methods h)r improving the coverage of examplebases were 1)reposed in order to allow the realization of broad-coverage examph&gt;l)ased systems. ~vV(, are evMuating our approacl) with larger amounts of data. For future progress, the following issues must be discussed: I. In this paper, conjunctive relationships were used as knowledge with the best-match algorithm, in addition to a thesaurus. However, various types of knowledge will be required on a large scale for a more robust system. Automatic or semi-mttomatic acquisition, using corpus-based methods, is also needed.</Paragraph>
    <Paragraph position="1"> 2. If there are many unknown words ill an all\]biguity, unknown-word matching will not work well. In additio,t to scaling up the example-base and the tlwsaurus, we should deve, top a nmre robust algorithm.</Paragraph>
  </Section>
class="xml-element"></Paper>