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<Paper uid="C04-1020">
  <Title>Representing discourse coherence: A corpus-based analysis</Title>
  <Section position="4" start_page="2" end_page="2" type="concl">
    <SectionTitle>
5 Conclusion
</SectionTitle>
    <Paragraph position="0"> The goals of this paper have been to present a set of coherence relations that are easy to code, and to illustrate the inadequacy of trees as a data structure for representing discourse coherence structures.</Paragraph>
    <Paragraph position="1"> We have developed a coding scheme with high inter-annotator reliability and used that scheme to annotate 135 texts with coherence relations. An investigation of these annotations has shown that discourse structures of naturally occurring texts contain various kinds of crossed dependencies as well as nodes with multiple parents. Both phenomena cannot be represented using trees, which implies that existing databases of coherence structures that use trees are not descriptively adequate.</Paragraph>
    <Paragraph position="2"> Our statistical results suggest that crossed dependencies and nodes with multiple parents are not restricted phenomena that could be ignored or accommodated with a few exception rules.</Paragraph>
    <Paragraph position="3"> Furthermore, even if one could find a way of augmenting tree structures to account for crossed dependencies and nodes with multiple parents, there would have to be a mechanism for unifying the tree structure with the augmentation features. Thus, in terms of derivational complexity, trees would just shift the burden from having to derive a less constrained data structure to having to derive a unification of trees and features or coindexation.</Paragraph>
    <Paragraph position="4"> Because trees are neither a descriptively adequate data structure for representing coherence structures nor easier to derive, we argue for less constrained graphs as a data structure for representing coherence structures. Such less constrained graphs would have the advantage of being able to adequately represent coherence structures in one single data structure (cf. Skut et al., 1997). Furthermore, they are at least not harder to derive than (augmented) tree structures.</Paragraph>
    <Paragraph position="5"> The greater descriptive adequacy might in fact make them easier to derive. However, this is still an open issue and will have to be addressed in future research.</Paragraph>
  </Section>
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