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<Paper uid="W96-0306">
  <Title>Acquisition of Semantic Lexicons: Using Word Sense Disambiguation to Improve Precision</Title>
  <Section position="7" start_page="47" end_page="47" type="concl">
    <SectionTitle>
6 Conclusion and Future Work
</SectionTitle>
    <Paragraph position="0"> Our main result is that the semantic field substantially reduces the number of incorrect assignments given by the syntactic filter. One of our goals is to assign new verbs, i.e., all of the verbs in LDOCE, to the semantic classes of Levin. Since there are 7767 verbs in LDOCE, and there are 191 semantic classes in Levin, there are 1,483,497 potential assignments of verbs to these semantic classes. The syntactic filter reduces the number of assignments under consideration to 113,106 (7.6% of the number of potential assignments) while preserving 67% of the assignments we know to be correct.</Paragraph>
    <Paragraph position="1"> The various semantic filters in turn reduce the number of assignments further. For example, the broad semantic filter reduced the 113,106 verbs that passed through the syntactic filter down to 6029 assignments, 19% of the number of assignments based on syntax and 0.4% of the potential assignments.</Paragraph>
    <Paragraph position="2"> Our goal throughout the acquisition task is to eliminate as many incorrect assignments as possible while preserving the correct assignments, and in this respect we are encouraged by the the behavior of the semantic filter on &amp;quot;unknown&amp;quot; verbs. Recall that to assess this behavior, we excluded randomly selected Levin verbs from the semantic filter, and saw how the filter behaved on these verbs.</Paragraph>
  </Section>
class="xml-element"></Paper>