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<Paper uid="C92-1030">
  <Title>An Empirical Study on Rule Granularity and Unification Interleaving Toward an Efficient Unification-Based Parsing System</Title>
  <Section position="8" start_page="0" end_page="0" type="concl">
    <SectionTitle>
7 Conclusion
</SectionTitle>
    <Paragraph position="0"> \]n this paper, we have proposed two techniques for implementing an efficient unification-based parsing system, which, when combined, significantly improve the overall performance. The first is changing the granularity of the context-free phrase structure rules into medium-grained rules. This enables us to reduce the amount of unification for feature descriptions without intractably increasing the number of phrase structure rules. The second is late unification in which the unification for feature descriptions is delayed until a complete CFG parse is found. This saves unnecessary copies of feature structures which are wasted for irrelevant subparses.</Paragraph>
    <Paragraph position="1"> We have tested the time behavior of the parsing system using two granunars of different granularity (coarse/medium) and two different strategies for invoking unification (early/late). It is proved that, on average, late unification using medium-grained rules parses 3.5 times fester than the previous early unification using coarse-grained rules.</Paragraph>
  </Section>
class="xml-element"></Paper>