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<Paper uid="E06-2026">
  <Title>Grammatical Role Labeling with Integer Linear Programming</Title>
  <Section position="9" start_page="189" end_page="189" type="concl">
    <SectionTitle>
8 Conclusion and Future Work
</SectionTitle>
    <Paragraph position="0"> In this paper, we argue for the integration of top down (theory based) information into NLP. One kind of information that is well known but have been used only in a data driven manner within statistical approaches (e.g. the Collins parser) is subcategorization information (or case frames). If subcategorization information turns out to be useful at all, it might become so only under the strict control of a global constraint mechanism. We are currently testing an ILP formalization where all subcategorization frames of a verb are competing witheachother. Thebenefits willbetohavetheinstantiation not only of licensed grammatical roles of a verb, but of a consistent and coherent instantiation of a single case frame.</Paragraph>
    <Paragraph position="1"> Acknowledgment. I would like to thank Markus Dreyer for fruitful (&amp;quot;long distance&amp;quot;) discussions and a number of (steadily improved) maximum entropy models. Also, the detailed comments of the reviewers have been very helpful.</Paragraph>
  </Section>
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