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<Paper uid="C04-1060">
  <Title>Syntax-Based Alignment: Supervised or Unsupervised?</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> Tree-based approaches to alignment model translation as a sequence of probabilistic operations transforming the syntactic parse tree of a sentence in one language into that of the other. The trees may be learned directly from parallel corpora (Wu, 1997), or provided by a parser trained on hand-annotated treebanks (Yamada and Knight, 2001). In this paper, we compare these approaches on Chinese-English and French-English datasets, and find that automatically derived trees result in better agreement with human-annotated word-level alignments for unseen test data.</Paragraph>
  </Section>
class="xml-element"></Paper>