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<Paper uid="P06-1006">
  <Title>Sydney, July 2006. c(c)2006 Association for Computational Linguistics Kernel-Based Pronoun Resolution with Structured Syntactic Knowledge</Title>
  <Section position="9" start_page="47" end_page="47" type="concl">
    <SectionTitle>
6 Conclusion
</SectionTitle>
    <Paragraph position="0"> The purpose of this paper is to explore how to make use of the structured syntactic knowledge to do pronoun resolution. Traditionally, syntactic information from parse trees is represented as a set of flat features. However, the features are usually selected and defined by heuristics and may not necessarily capture all the syntactic information provided by the parse trees. In the paper, we propose a kernel-based method to incorporate the information from parse trees. Specifically, we directly utilize the syntactic parse tree as a structured feature, and then apply kernels to such a feature, together with other normal features, to learn the decision classifier and do the resolution. Our experimental results on ACE data set show that the system with the structured feature included can achieve significant increase in the success rate by around 5%[?]8%, for all the different domains.</Paragraph>
    <Paragraph position="1"> The deeper analysis on various factors like training size, feature set or parsers further proves that the structured feature incorporated with our kernel-based method is reliably effective for the pronoun resolution task.</Paragraph>
  </Section>
class="xml-element"></Paper>