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<Paper uid="P04-1020">
  <Title>Learning Noun Phrase Anaphoricity to Improve Coreference Resolution: Issues in Representation and Optimization</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> Knowledge of the anaphoricity of a noun phrase might be profitably exploited by a coreference system to bypass the resolution of non-anaphoric noun phrases. Perhaps surprisingly, recent attempts to incorporate automatically acquired anaphoricity information into coreference systems, however, have led to the degradation in resolution performance.</Paragraph>
    <Paragraph position="1"> This paper examines several key issues in computing and using anaphoricity information to improve learning-based coreference systems. In particular, we present a new corpus-based approach to anaphoricity determination. Experiments on three standard coreference data sets demonstrate the effectiveness of our approach.</Paragraph>
  </Section>
class="xml-element"></Paper>