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<Paper uid="A00-2015">
  <Title>Analyzing Dependencies of Japanese Subordinate Clauses based on Statistics of Scope Embedding Preference</Title>
  <Section position="3" start_page="235" end_page="235" type="intro">
    <SectionTitle>
3.5 Example
</SectionTitle>
    <Paragraph position="0"> Figure 4 illustrates an example of transforming subordinate clauses into feature expression, and then obtaining training pairs of an evidence and a decision from a bracketed sentence. Figure 4 (a) shows an example sentence which contains two subordinate clauses Clause1 and Clause2, with chunking, bracketing, and dependency relations of chunks. Both of the head vp chunks Segl and Seg2 of Clause1 and Clause2 modify the sentence-final vp chunk. As shown in Figure 4 (b), the head vp chunks Segl and Seg2 have feature sets ~'1 and ~'2, respectively. Then, every possible subsets F1 and F2 of ~1 and ~2 are considered, n respectively, and training pairs of an evidence and a decision are collected as in Figure 4 (c). In this case, the value of the decision D is &amp;quot;beyond&amp;quot;, because Segl modifies the sentence-final vp chunk, which follows Seg 2.</Paragraph>
    <Paragraph position="1"> 1degOur formalization of the evidence of decision list learning has an advantage over the decision tree learning (Quinlan, 1993) approach to feature selection of dependency analysis (Haruno et al., 1998). In the feature selection procedure of the decision tree learning method, the utility of each feature is evaluated independently, and thus the utility of the combination of more than one features is not evaluated directly. On the other hand, in our formalization of the evidence of decision list learning, we consider every possible pair of the subsets F1 and Fz, and thus the utility of the combination of more than one features is evaluated directly.</Paragraph>
    <Paragraph position="2"> lXSince the feature 'predicate-conjunctiveparticle(chunk-final)' subsumes 'predicate-conjunctiveparticle(chunk-final)-&amp;quot;ga&amp;quot;, they are not considered together as one evidence.</Paragraph>
  </Section>
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