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<Paper uid="W04-0208">
  <Title>Temporal Discourse Models for Narrative Structure</Title>
  <Section position="8" start_page="0" end_page="0" type="concl">
    <SectionTitle>
7 Conclusion
</SectionTitle>
    <Paragraph position="0"> Our assumption so far has been that the temporal structure of narratives is tree-structured and context-free. Whether the context-free property is violated or not remains to be seen.</Paragraph>
    <Paragraph position="1"> Once the annotation effort is completed, we plan to use the annotated corpora in statistical parsing algorithms to construct TDMs. This should allow features from the corpus to be leveraged together to make inferences about narrative structure. While such knowledge source combination is not by any means guaranteed to substitute for commonsense knowledge, it at least allows for the introduction of generic, machine learning methods for extracting narrative structure from stories in any domain. Earlier work in a noncorpus based (Hitzeman et al. 1995) as well as corpus-based setting (Mani et al. 2003) attests to the usefulness of combining knowledge sources for inferring temporal relations. We expect to leverage similar methods in TDM parsing.</Paragraph>
    <Paragraph position="2"> We believe that the temporal aspect of discourse provides a handle for investigating discourse structure, thereby simplifying the problem of discourse structure annotation. It is therefore of considerable theoretical interest.</Paragraph>
    <Paragraph position="3"> Further, being able to understand the structure of narratives will in turn allow us to summarize them and answer temporal questions about narrative structure.</Paragraph>
  </Section>
class="xml-element"></Paper>