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<Paper uid="W05-1511">
  <Title>Vancouver, October 2005. c(c)2005 Association for Computational Linguistics Efficacy of Beam Thresholding, Unification Filtering and Hybrid Parsing in Probabilistic HPSG Parsing</Title>
  <Section position="7" start_page="111" end_page="112" type="concl">
    <SectionTitle>
6 Conclusion
</SectionTitle>
    <Paragraph position="0"> We have described the results of experiments with a number of existing techniques in head-driven phrase  structure grammar (HPSG) parsing. Simple beam thresholding, similar to that for probabilistic CFG (PCFG) parsing, significantly increased the parsing speed over Viterbi algorithm, but reduced the recall because of parsing failure. Iterative parsing significantly increased the parsing speed without degrading precision or recall. We tested three techniques originally developed for deep parsing: quick check, large constituent inhibition, and HPSG parsing with a CFG chunk parser. The contributions of the large constituent inhibition and global thresholding were not significant, while the quick check and chunk parser greatly contributed to total parsing performance. The precision, recall and average parsing time for the Penn treebank (Section 23) were 87.85%, 86.85%, and 360 ms, respectively.</Paragraph>
  </Section>
class="xml-element"></Paper>