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<Paper uid="P04-1058">
  <Title>Alternative Approaches for Generating Bodies of Grammar Rules</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We compare two approaches for describing and generating bodies of rules used for natural language parsing. In today's parsers rule bodies do not exist a priori but are generated on the fly, usually with methods based on n-grams, which are one particular way of inducing probabilistic regular languages. We compare two approaches for inducing such languages. One is based on n-grams, the other on minimization of the Kullback-Leibler divergence. The inferred regular languages are used for generating bodies of rules inside a parsing procedure. We compare the two approaches along two dimensions: the quality of the probabilistic regular language they produce, and the performance of the parser they were used to build. The second approach outperforms the first one along both dimensions.</Paragraph>
  </Section>
class="xml-element"></Paper>