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<Paper uid="W96-0305">
  <Title>Acquisition of Computational-Semantic Lexicons from Machine Readable Lexicai Resources</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper describes a heuristic algorithm capable of automatically assigning a label to each of the senses in a machine readable dictionary (MRD) for the purpose of acquiring a computational-semantic lexicon for treatment of lexical ambiguity. Including these labels in the MRD-based lexical database offers several positive effects. The labels can be used as a coarser sense division so unnecessarily fine sense distinction can be avoided in word sense disambiguation (WSD).The algorithm is based primarily on simple word matching between an MRD definition sentence and word lists of an LLOCE topic. We also describe an implementation of the algorithm for labeling definition sentences in Longman Dictionary of Contemporary English (LDOCE). For this purpose the topics and sets of related words in Longman Lexicon of Contemporary English (LLOCE) are used in this work. Quantitative results for a 12-word test set are reported. Our discussion entails how the availability of these labels provides the means for treating such problems as: acquisition of a lexicon capable of providing broad coverage, systematic word sense shifts, lexical underspecification, and acquisition of zero-derivatives.</Paragraph>
  </Section>
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