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<Paper uid="J05-2005">
  <Title>Representing Discourse Coherence: A Corpus-Based Study</Title>
  <Section position="5" start_page="467" end_page="467" type="concl">
    <SectionTitle>
5. Conclusion
</SectionTitle>
    <Paragraph position="0"> The goals of this article 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. We have developed a coding scheme with high interannotator reliability and used that scheme to annotate 135 texts with coherence relations.</Paragraph>
    <Paragraph position="1"> 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. Neither phenomenon can be represented using trees. This 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. 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="3"> 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. In particular, we argue for a representation such as chain graphs (cf. final paragraph of section 3). Such less constrained graphs would have the advantage of being able to adequately represent coherence structures in one single data structure (cf. Brants et al. 2002; Skut et al. 1997; K&amp;quot;onig and Lezius 2000).  Wolf and Gibson Representing Discourse Coherence Furthermore, they are at least not harder to derive than (augmented) tree structures.</Paragraph>
    <Paragraph position="4"> 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>
    <Paragraph position="5"> In section 2.3 we briefly illustrated the possibility of more-fine-grained discourse segmentation than in the current project. Although such a detailed annotation of coherence relations was beyond the scope of the current project, future research should address this issue. More-fine-grained discourse segmentation could then also facilitate integration of discourse-level with sentence-level structural descriptions.</Paragraph>
    <Paragraph position="6"> Another issue that should be addressed in future research is empirically viable constraints on inferences for building discourse structures. As pointed out in section 3, even though we have argued against trees as a data structure for representing discourse structures, that does not necessarily mean that discourse structures can be completely arbitrary. Future research should investigate questions such as whether there are structural constraints on coherence graphs (e.g., as proposed by Danlos [2004]) or whether there are systematic structural differences between the coherence graphs of texts that belong to different genres (e.g., as proposed by Bergler [1991]).</Paragraph>
  </Section>
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