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<Paper uid="W98-0701">
  <Title>I I I I I I 1 General Word Sense Disambiguation Method Based on a Full Sentential Context</Title>
  <Section position="10" start_page="7" end_page="7" type="concl">
    <SectionTitle>
9 Conclusion
</SectionTitle>
    <Paragraph position="0"> This paper presents a new general approach to word sense disambiguation. Unlike most of the existing methods, it identifies the senses of all content words in a sentence based on an estimation of the overall probability of all semantic relations in that sentence.</Paragraph>
    <Paragraph position="1"> By using the semantic distance measure, our method reduces the sparse data problem since the training examples and their contexts do not have to match the disambiguated words exactly. All the semantic relations in a sentence are combined according to the syntactic structure of the sentence, which makes the method particularly suitable for integration with a statistical parser into a powerful Natural Language Processing system. The method is designed to work with any type of common text and is capable of distinguishing among many word senses. It has a very wide scope of applicability and is not limited to only one part-of-speech.</Paragraph>
  </Section>
class="xml-element"></Paper>