<?xml version="1.0" standalone="yes"?>
<Paper uid="P97-1009">
  <Title>Using Syntactic Dependency as Local Context to Resolve Word Sense Ambiguity</Title>
  <Section position="8" start_page="69" end_page="69" type="concl">
    <SectionTitle>
6 Conclusion
</SectionTitle>
    <Paragraph position="0"> We have presented a new algorithm for word sense disambiguation. Unlike most previous corpus-based WSD algorithm where separate classifiers are trained for different words, we use the same local context database and a concept hierarchy as the knowledge sources for disambiguating all words.</Paragraph>
    <Paragraph position="1"> This allows our algorithm to deal with infrequent words or unknown proper nouns.</Paragraph>
    <Paragraph position="2"> Unnecessarily subtle distinction between word senses is a well-known problem for evaluating WSD algorithms with general-purpose lexical resources.</Paragraph>
    <Paragraph position="3"> Our use of similarity measure to relax the correctness criterion provides a possible solution to this problem.</Paragraph>
  </Section>
class="xml-element"></Paper>