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<Paper uid="W05-0602">
  <Title>A Statistical Semantic Parser that Integrates Syntax and Semantics</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We introduce a learning semantic parser, SCISSOR, that maps natural-language sentences to a detailed, formal, meaning-representation language. It first uses an integrated statistical parser to produce a semantically augmented parse tree, in which each non-terminal node has both a syntactic and a semantic label.</Paragraph>
    <Paragraph position="1"> A compositional-semantics procedure is then used to map the augmented parse tree into a final meaning representation.</Paragraph>
    <Paragraph position="2"> We evaluate the system in two domains, a natural-language database interface and an interpreter for coaching instructions in robotic soccer. We present experimental results demonstrating that SCISSOR produces more accurate semantic representations than several previous approaches.</Paragraph>
  </Section>
class="xml-element"></Paper>