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<Paper uid="P98-1034">
  <Title>Error-Driven Pruning of Treebank Grammars for Base Noun Phrase Identification</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> Finding simple, non-recursive, base noun phrases is an important subtask for many natural language processing applications. While previous empirical methods for base NP identification have been rather complex, this paper instead proposes a very simple algorithm that is tailored to the relative simplicity of the task. In particular, we present a corpus-based approach for finding base NPs by matching part-of-speech tag sequences. The training phase of the algorithm is based on two successful techniques: first the base NP grammar is read from a &amp;quot;treebank&amp;quot; corpus; then the grammar is improved by selecting rules with high &amp;quot;benefit&amp;quot; scores. Using this simple algorithm with a naive heuristic for matching rules, we achieve surprising accuracy in an evaluation on the Penn Treebank Wall Street Journal.</Paragraph>
  </Section>
class="xml-element"></Paper>