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<Paper uid="N04-4037">
  <Title>A Lightweight Semantic Chunking Model Based On Tagging</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> In this paper, a framework for the development of a fast, accurate, and highly portable semantic chunker is introduced. The framework is based on a non-overlapping, shallow tree-structured language. The derivation of the tree is considered as a sequence of tagging actions in a predefined linguistic context, and a novel semantic chunker is accordingly developed. It groups the phrase chunks into the arguments of a given predicate in a bottom-up fashion. This is quite different from current approaches to semantic parsing or chunking that depend on full statistical syntactic parsers that require tree bank style annotation. We compare it with a recently proposed word-by-word semantic chunker and present results that show that the phrase-by-phrase approach performs better than its word-by-word counterpart. null</Paragraph>
  </Section>
class="xml-element"></Paper>