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<Paper uid="W06-0138">
  <Title>Using Part-of-Speech Reranking to Improve Chinese Word Segmentation</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> Chinese word segmentation and Part-of-Speech (POS) tagging have been commonly considered as two separated tasks.</Paragraph>
    <Paragraph position="1"> In this paper, we present a system that performs Chinese word segmentation and POS tagging simultaneously. We train a segmenter and a tagger model separately based on linear-chain Conditional Random Fields (CRF), using lexical, morphological and semantic features. We propose an approximated joint decoding method by reranking the N-best segmenter output, based POS tagging information. Experimental results on SIGHAN Bakeoff dataset and Penn Chinese Treebank show that our reranking method significantly improve both segmentation and POS tagging accuracies.</Paragraph>
  </Section>
class="xml-element"></Paper>