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<Paper uid="A00-2021">
  <Title>Exploiting auxiliary distributions in stochastic unification-based grammars</Title>
  <Section position="7" start_page="159" end_page="159" type="concl">
    <SectionTitle>
6 Conclusion
</SectionTitle>
    <Paragraph position="0"> This paper has presented a method for incorporating auxiliary distributional information gathered by other means possibly from other corpora into a Stochastic &amp;quot;Unification-based&amp;quot; Grammar (SUBG). This permits one to incorporate dependencies into a SUBG which probably cannot be estimated directly from the small UBG parsed corpora available today. It has the virtue that it can incorporate several auxiliary distributions simultaneously, and because it associates each auxiliary distribution with its own &amp;quot;weight&amp;quot; parameter, it can scale the contributions of each auxiliary distribution toward the final estimated distribution, or even ignore it entirely. We have applied this to incorporate lexical selectional preference information into a Stochastic Lexical-Functional Grammar, but the technique generalizes to stochastic versions of HPSGs, categorial grammars and transformational grammars. An obvious extension of this work, which we hope will be persued in the future, is to apply these techniques in broad-coverage feature-based TAG parsers.</Paragraph>
  </Section>
class="xml-element"></Paper>