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<Paper uid="W04-0854">
  <Title>KUNLP System in SENSEVAL-3</Title>
  <Section position="8" start_page="6" end_page="6" type="concl">
    <SectionTitle>
4 Conclusions
</SectionTitle>
    <Paragraph position="0"> In SENSEVAL-3, we participated in both English all words task and English lexical sample task with an unsupervised system based on WordNet and a raw corpus, which did not use any sense tagged corpus. Our system disambiguated the senses of a target word by selecting a substituent among WordNet relatives of the target word, which frequently co-occurs with each word surrounding the target word in a context. Since each relative is usually related to only one sense of the target word, our system identifies the proper sense with the selected relative. The substituent word is selected based on the co-occurrence frequency between the relative and the words surrounding the target word in a given context. We collected the co-occurrence frequency from a raw corpus, not a sense-tagged one that is often required by other approaches. In short, our system disambiguates senses of words only through the set of WordNet relatives of the target words and a raw corpus. The system was simple but seemed to achieve a good performance when considered the performance of systems in last SENSEVAL-2 English tasks.</Paragraph>
    <Paragraph position="1"> For future research, we will investigate the dependency between the types of relatives and the characteristics of words or senses in order to devise an improved method that better utilizes various types of relatives for WSD.</Paragraph>
  </Section>
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