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<Paper uid="N06-1055">
  <Title>Semantic Role Labeling of Nominalized Predicates in Chinese</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> Recent work on semantic role labeling (SRL) has focused almost exclusively on the analysis of the predicate-argument structure of verbs, largely due to the lack of human-annotated resources for other types of predicates that can serve as training and test data for the semantic role labeling systems. However, it is well-known that verbs are not the only type of predicates that can take arguments.</Paragraph>
    <Paragraph position="1"> Most notably, nouns that are nominalized forms of verbs and relational nouns generally are also considered to have their own predicate-argument structure. In this paper we report results of SRL experiments on nominalized predicates in Chinese, using a newly completed corpus, the Chinese Nombank. We also discuss the impact of using publicly available manually annotated verb data to improve the SRL accuracy of nouns, exploiting a widely-held assumption that verbs and their nominalizations share the same predicate-argument structure. Finally, we discuss the results of applying reranking techniques to improve SRL accuracy for nominalized predicates, which showed insignificant improvement.</Paragraph>
  </Section>
class="xml-element"></Paper>