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<Paper uid="W04-2419">
  <Title>Semantic Role Labeling using Maximum Entropy Model</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> In this paper, we propose a semantic role labeling method using a maximum entropy model, which enables not only to exploit rich features but also to alleviate the data sparseness problem in a well-founded model. For applying the maximum entropy model to semantic role labeling, we take a incremental approach as follows: firstly, the semantic roles are assigned to the arguments in the immediate clause including a predicate, and then, the semantic roles are assigned to the arguments in the upper clauses by using previously assigned labels. The experimental result shows that the proposed method has about 64.76% (F1-measure) on the test set.</Paragraph>
  </Section>
class="xml-element"></Paper>