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<Paper uid="P97-1020">
  <Title>Deriving Verbal and Compositional Lexical Aspect for NLP Applications</Title>
  <Section position="9" start_page="156" end_page="156" type="concl">
    <SectionTitle>
7 Conclusion
</SectionTitle>
    <Paragraph position="0"> The privative feature model, on which our LCS composition draws, allows us to represent verbal and sentential lexical aspect as monotonic composition of the same type, and to identify the contribution of both verbs and other elements. The lexical aspect of verbs and sentences may be therefore determined from the corresponding LCS representations, as in the examples provided from machine translation and foreign language tutoring applications. We are aware of no attempt in the literature to represent and access aspect on a similar scale, in part, we suspect, because of the difficulty of identifying the aspectual contribution of the verbs and sentences given the multiple aspectual types in which verbs appear.</Paragraph>
    <Paragraph position="1"> An important corollary to this investigation is that it is possible to refine the lexicon, because variable meaning may, in many cases, be attributed to lexical aspect variation predictable by composition rules. In addition, factoring out the structural requirements of specific lexical items from the predictable variation that may be described by composition provides information on the aspectual effect of verbal modifiers and complements. We are therefore able to describe not only the lexical aspect at the sentential level, but also the set of aspectual variations available to a given verb type.</Paragraph>
  </Section>
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