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Representing Discourse Coherence: A Corpus-Based Study

Summary

The paper addresses two linked questions in discourse analysis: which informational coherence relations between text segments people can annotate reliably, and what data structure is needed to store them. The authors set intentional structure aside and focus on how the meanings of segments relate. They use a compact relation inventory largely derived from Hobbs (1985). Segmentation is mostly clause-based, with boundaries marked by punctuation, contentful conjunctions and attributions. Adjacent segments can also be grouped by topic, source or temporal ordering. The scheme was applied to 135 news articles drawn from two sources, the AP Newswire and the Wall Street Journal. Two annotators labeled every text independently and reached high agreement (Kappa above 0.8). The authors deliberately did not assume a tree. The resulting coherence graphs show frequent crossed dependencies and many nodes with more than one parent. This challenges tree-based frameworks such as RST and supports more general graph representations for discourse corpora and parsers.

Key points

  • Corpus: 135 hand-annotated news texts, sourced from the AP Newswire and the Wall Street Journal, each coded by two independent annotators, with Kappa values greater than 0.8.
  • Relation types include cause–effect (directed from cause to effect), condition, violated expectation, similarity, contrast, temporal sequence, attribution, example, elaboration and generalization. Contentful conjunctions such as "because", "although" and "for example" serve as cues for these relations.
  • The scheme departs from Hobbs (1985) in two ways. It merges his cause and explanation relations into one directed cause–effect relation, and it separates condition (a possible causal link) from actual causation.
  • The scheme permitted partially overlapping segment groups, but annotators never used this option in any of the 135 texts.
  • Main finding: trees are descriptively inadequate for discourse coherence, because naturally occurring texts contain many crossed dependencies and multi-parent nodes. Statistics from the annotated database support this claim.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: Linguistics & languages

Topics: Discourse analysis

Cited by

74 papers of our library cite it (of the 140673 whose bibliographies we read); 12 of them have a page here, 62 not yet.

Cite

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.1162/0891201054223977

@article{wolf2005representing,
  title = {{Representing Discourse Coherence: A Corpus-Based Study}},
  author = {Wolf, Florian and Gibson, Edward},
  journal = {Computational Linguistics},
  year = {2005},
  doi = {10.1162/0891201054223977},
  url = {https://doi.org/10.1162/0891201054223977}
}

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