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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="8" start_page="5" end_page="5" type="evalu">
    <SectionTitle>
7 Evaluation
</SectionTitle>
    <Paragraph position="0"> To evaluate the algorithm, we randomly selected 15 files (with a total of 18,413 content words tagged in SemCor) from the set of 103 files of the sense tagged section of the Brown Corpus. Each tested file was removed from the set and the remaining 102 files were used for learning (Section 4). Every sense assigned by the hierarchical disambiguation algorithm (Section 5) was compared with the sense from the corresponding semantic concordance file. Table 4 shows the achieved accuracy compared with the accuracy which would be achieved by a simple use of the most frequent sense.</Paragraph>
    <Paragraph position="1"> As the above table shows, the accuracy of the word sense disambiguation achieved by our method was better than using the first sense for all lexicai categories. In spite of a very small training corpus, the overall word sense accuracy exceeds 80%.</Paragraph>
  </Section>
class="xml-element"></Paper>