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<Paper uid="W05-1505">
  <Title>Corrective Modeling for Non-Projective Dependency Parsing</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We present a corrective model for recovering non-projective dependency structures from trees generated by state-of-the-art constituency-based parsers. The continuity constraint of these constituency-based parsers makes it impossible for them to posit non-projective dependency trees. Analysis of the types of dependency errors made by these parsers on a Czech corpus show that the correct governor is likely to be found within a local neighborhood of the governor proposed by the parser. Our model, based on a MaxEnt classifier, improves overall dependency accuracy by .7% (a 4.5% reduction in error) with over 50% accuracy for non-projective structures.</Paragraph>
  </Section>
class="xml-element"></Paper>