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<Paper uid="W06-2927">
  <Title>Multi-lingual Dependency Parsing at NAIST</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> In this paper, we present a framework for multi-lingual dependency parsing. Our bottom-up deterministic parser adopts Nivre's algorithm (Nivre, 2004) with a preprocessor. Support Vector Machines (SVMs) are utilized to determine the word dependency attachments. Then, a maximum entropy method (MaxEnt) is used for determining the label of the dependency relation. To improve the performance of the parser, we construct a tagger based on SVMs to find neighboring attachment as a preprocessor. Experimental evaluation shows that the proposed extension improves the parsing accuracy of our base parser in 9 languages. (Hajic et al., 2004; Simov et al., 2005; Simov and Osenova, 2003; Chen et al., 2003; Bohmova et al., 2003; Kromann, 2003; van der Beek et al., 2002; Brants et al., 2002; Kawata and Bartels, 2000; Afonso et al., 2002; Dzeroski et al., 2006; Civit and Marti, 2002; Nilsson et al., 2005; Oflazer et al., 2003; Atalay et al., 2003).</Paragraph>
  </Section>
class="xml-element"></Paper>