---
title: "Representing discourse coherence — Wolf 2004"
description: "Most theories of discourse structure, and the resources built on them, represent coherence as a tree."
authors: ["Florian Wolf", "Edward Gibson"]
year: 2004
venue: "COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics"
source: "https://aclanthology.org/C04-1020/"
licence: "CC BY-NC-SA 3.0 (ACL Anthology, before 2016)"
licence_url: "https://creativecommons.org/licenses/by-nc-sa/3.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/wolf-2004-representing-discourse-coherence-corpus-based/"
---
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# Representing discourse coherence: A corpus-based analysis

**Authors:** [Florian Wolf](https://md.research.elamur.ai/free/en/authors/florian-wolf/), [Edward Gibson](https://md.research.elamur.ai/free/en/authors/edward-gibson/) · **Year:** 2004 · **Venue:** COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics · **Licence:** [CC BY-NC-SA 3.0 (ACL Anthology, before 2016)](https://creativecommons.org/licenses/by-nc-sa/3.0/)

**Links:** [Publisher's page](https://aclanthology.org/C04-1020/) · [PDF](https://aclanthology.org/C04-1020.pdf) · [OpenAlex](https://openalex.org/W7098884861)

**Citations:** 0 citations (openalex-snapshot · 2026-10-14) · [16](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary
Most theories of discourse structure, and the resources built on them, represent coherence as a tree. Wolf and Gibson test whether that assumption holds for real texts. They propose a compact, easy-to-apply set of coherence relations largely derived from Hobbs (1985). The set covers cause-effect, violated expectation, condition, similarity, contrast, elaboration, attribution, temporal sequence and "same". Annotators split each text into segments at sentences and contentful conjunctions, then grouped topically related segments. Finally, they linked segments and groups, checking each candidate relation by inserting a signalling conjunction. Using this scheme, 135 Wall Street Journal and AP Newswire texts were each annotated by two people, with high reliability. The resulting graphs frequently contain crossed dependencies and nodes with more than one parent, and neither can be expressed in a tree. These phenomena involve all relation types and mostly occur over short distances. The authors therefore argue for less constrained labeled directed graphs as the representation of discourse coherence. Their findings also call into question the descriptive adequacy of tree-based discourse corpora.

## Key points
- The corpus contains 135 texts from WSJ (1987–1989) and AP Newswire (1989). Texts average 545 words and 61 discourse segments.
- Each text was annotated independently by two annotators. Raw agreement was 88.45% and kappa was 84.63%, with no dependence on text length, arc length or relation type.
- On average a node has 1.6 parents, with a maximum of 12. In total, 41% of nodes have more than one incoming relation.
- Any relation type can take part in crossed dependencies, though some do so much less often. "Same" relations are about 15 times rarer in crossings than overall, and condition relations about 6 times rarer.
- Arc-length distributions for crossed and multi-parent arcs closely mirror the overall distribution (R² ≈ 0.94–0.99), which indicates a strong locality bias.

*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](https://md.research.elamur.ai/free/en/shelves/linguistics/)

Topics: [Discourse analysis](https://md.research.elamur.ai/free/en/topics/discourse-analysis/)

## Cited by

Cited by

16 papers of our library cite it (of the 140673 whose bibliographies we read); 6 of them have a page here, 10 not yet.

- [Analyses of the Association between Discourse Relation and Sentiment Polarity with a Chinese Human-Annotated Corpus](https://md.research.elamur.ai/free/en/papers/huang-2013-analyses-association-between-discourse-relation/)
- [Recognizing Implicit Discourse Relations in the Penn Discourse Treebank](https://md.research.elamur.ai/free/en/papers/lin-2009-recognizing-implicit-discourse-relations-penn/)
- [The Rhetorical Structure of Attribution](https://md.research.elamur.ai/free/en/papers/potter-2019-rhetorical-structure-attribution/)
- [Unpacking Ambiguous Structure: A Dataset for Ambiguous Implicit Discourse Relations for English and Egyptian Arabic](https://md.research.elamur.ai/free/en/papers/ruby-2023-unpacking-ambiguous-structure-dataset-ambiguous/)
- [An effective Discourse Parser that uses Rich Linguistic Information](https://md.research.elamur.ai/free/en/papers/subba-2009-effective-discourse-parser-that-uses/)
- [Classification of Discourse Coherence Relations: An Exploratory Study using Multiple Knowledge Sources](https://md.research.elamur.ai/free/en/papers/wellner-2006-classification-discourse-coherence-relations-exploratory/)

## Cite

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

```bibtex
@inproceedings{wolf2004representing,
  title = {{Representing discourse coherence: A corpus-based analysis}},
  author = {Wolf, Florian and Gibson, Edward},
  booktitle = {COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics},
  year = {2004},
  url = {https://aclanthology.org/C04-1020/}
}
```

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