<?xml version="1.0" standalone="yes"?>
<Paper uid="C00-1010">
  <Title>An Empirical Evaluation of LFG-DOP</Title>
  <Section position="5" start_page="67" end_page="67" type="concl">
    <SectionTitle>
4 Conclusion
</SectionTitle>
    <Paragraph position="0"> We have given an empirical assessment of the LFG-DOP model introduced by Bed &amp; Kaplan (1998). We developed a new probability model for LFG-DOP which treats fragments with generalized features as previously unseen events. The experiments showed that our probability model outperforms Bed &amp; Kaplan's model on the Verbmobil and Homeceutre corpora. Moreover, Bed &amp; Kaplan's model turned out to be inadequate in dealing with generalized fragments. We also established that the contribution of generalized fragments to the parse accuracy in our model is minimal and statistically insignil'icant. Finally, we showed that LFG's l'unctional structures contribute to significantly higher parse accuracy on tree structures. This suggests that our model may be successfully used to exploit the functional annotations in the Penn Treebank (Marcus et al. 1994), provided that these annotations can be converted into LFG-style l'unctional structures. As future research, we want to test LFG-DOP using log-linear models, as such models maximize the likelihood o1' the traiuing corpus.</Paragraph>
  </Section>
class="xml-element"></Paper>