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<Paper uid="P97-1009">
  <Title>Using Syntactic Dependency as Local Context to Resolve Word Sense Ambiguity</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> Most previous corpus-based algorithms disambiguate a word with a classifier trained from previous usages of the same word.</Paragraph>
    <Paragraph position="1"> Separate classifiers have to be trained for different words. We present an algorithm that uses the same knowledge sources to disambiguate different words. The algorithm does not require a sense-tagged corpus and exploits the fact that two different words are likely to have similar meanings if they occur in identical local contexts.</Paragraph>
  </Section>
class="xml-element"></Paper>