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<Paper uid="N01-1009">
  <Title>A Corpus-based Account of Regular Polysemy: The Case of Context-sensitive Adjectives</Title>
  <Section position="6" start_page="2" end_page="2" type="concl">
    <SectionTitle>
5 Conclusions
</SectionTitle>
    <Paragraph position="0"> In this paper we showed how adjectival meanings can be acquired from a large corpus and provided a probabilistic model which derives a preference ordering on the set of possible interpretations. Our model does not only acquire clusters of meanings (following Vendler's (1968) insight) but furthermore can be used to obtain argument preferences for a given adjective.</Paragraph>
    <Paragraph position="1"> We rigorously evaluated the results of our model by eliciting paraphrase judgments from subjects naive to linguistic theory. Comparison between our model and human judgments yielded a reliable correlation of :40 when the upper bound for the task (i.e., inter-subject agreement) is approximately :65. Furthermore, our model performed reliably better than a naive baseline model, which only achieved a correlation of :25. Although adjective-noun polysemy is a well researched phenomenon in the theoretical linguistics literature, the experimental approach advocated here is new to our knowledge.</Paragraph>
    <Paragraph position="2"> Furthermore, the proposed model can be viewed as complementary to linguistic theory: it automatically derives a ranking of meanings, thus distinguishing likely from unlikely interpretations. Even if linguistic theory was able to enumerate all possible interpretations for a given adjective (note that in the case of polysemous adjectives we would have to take into account all nouns or noun classes the adjective could possibly modify) it has no means to indicate which ones are likely and which ones are not. Our model fares well on both tasks.</Paragraph>
    <Paragraph position="3"> It recasts the problem of adjective-noun polysemy in a probabilistic framework deriving a large number of interpretations not readily available from linguistic introspection. The information acquired from the corpus can be also used to quantify the argument preferences of a given adjective. These are only implicit in the lexical semantics literature where certain adjectives are exclusively given a verb-subject or verb-object interpretation. We have demonstrated that we can empirically derive argument biases for a given adjective that correspond to human intuitions.</Paragraph>
  </Section>
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