---
title: "What excludes an Alternative in Coherence — Webber 2013"
description: "The paper asks what linguistic signals mark one argument of a coherence relation as an alternative that the discourse sets aside."
authors: ["Bonnie Webber"]
year: 2013
venue: "Proceedings of the 10th International Conference on Computational Semantics (IWCS 2013) – Long Papers"
source: "https://aclanthology.org/W13-0124/"
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/papers/webber-2013-what-excludes-alternative-coherence-relations/"
---
[Elamur Research](https://md.research.elamur.ai/) · [this page in HTML](https://research.elamur.ai/free/papers/webber-2013-what-excludes-alternative-coherence-relations/)

[home](https://md.research.elamur.ai/) / [papers](https://md.research.elamur.ai/free/papers/) / [2013](https://md.research.elamur.ai/free/papers/2013/page/2/) / What excludes an Alternative in Coherence Relations?

# What excludes an Alternative in Coherence Relations?

**Authors:** [Bonnie Webber](https://md.research.elamur.ai/free/authors/bonnie-webber/) · **Year:** 2013 · **Venue:** Proceedings of the 10th International Conference on Computational Semantics (IWCS 2013) – Long Papers · **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/W13-0124/) · [PDF](https://aclanthology.org/W13-0124.pdf) · [OpenAlex](https://openalex.org/W2150264005)

**Citations:** 12 citations (openalex-snapshot · 2026-10-14) · [12](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary

The paper asks what linguistic signals mark one argument of a coherence relation as an alternative that the discourse sets aside. It focuses on the CHOSEN ALTERNATIVE sense of the Penn Discourse TreeBank 2.0 (PDTB 2.0). Recognizing discourse relations without an overt connective remains hard. Webber argues that better features will help more than new learning algorithms. She uses the connective *instead* as an almost unambiguous marker of this sense. Drawing on PDTB 2.0 and a separate hand-collected Instead Corpus, she catalogues the constructions that appear in Arg1, which supplies the rejected option. The most frequent are negation, downward-entailing (DE) predicates and event modals. Less common licensers include state-expecting verbs and non-factual *if* clauses. These cues show up even more often when the CHOSEN ALTERNATIVE relation is implicit than when it is explicitly signalled. When strong cues are present, the connective is often omitted. When the evidence is subtle, a connective tends to appear. This makes the features promising for identifying implicit relations and their arguments automatically.

## Key points

- PDTB 2.0 contains more than 40K manually annotated relations over the Wall Street Journal corpus. Of its 112 tokens of *instead*, 108 are labelled EXPANSION.ALTERNATIVE.CHOSEN ALTERNATIVE. The author argues the remaining four also belong to this sense.
- A supplementary, singly-annotated Instead Corpus of more than 300 tokens provides additional evidence.
- The frequency of each feature in implicit relations (171 tokens) versus explicit relations (118 tokens) is:

  | Feature | Implicit | Explicit |
  |---|---|---|
  | Negation | 67.8% | 39.8% |
  | DE predicates | 14.0% | 15.3% |
  | Event modals | 5.3% | 11.0% |
  | Other | 12.9% | 33.9% |

- About 87% of implicit CHOSEN ALTERNATIVE relations contain at least one of the three main features.
- These cues also occur in other relations, such as temporal and causal ones. They are therefore not sufficient on their own, but their absence counts as evidence against a candidate Arg1.

*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/shelves/linguistics/)

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

## Cited by

Cited by

12 papers of our library cite it (of the 140673 whose bibliographies we read); 5 of them have a page here, 7 not yet.

- [On the Information Conveyed by Discourse Markers](https://md.research.elamur.ai/free/papers/asr-2013-information-conveyed-discourse-markers/)
- [Reflections on the Penn Discourse TreeBank, Comparable Corpora, and Complementary Annotation](https://md.research.elamur.ai/free/papers/prasad-2014-reflections-penn-discourse-treebank-comparable/)
- [Discourse Coherence: Concurrent Explicit and Implicit Relations](https://md.research.elamur.ai/free/papers/rohde-2018-discourse-coherence-concurrent-explicit-implicit/)
- [Examples and Specifications that Prove a Point: Identifying Elaborative and Argumentative Discourse Relations](https://md.research.elamur.ai/free/papers/scholman-2017-examples-specifications-that-prove-point/)
- [eRST: A Signaled Graph Theory of Discourse Relations and Organization](https://md.research.elamur.ai/free/papers/zeldes-2025-erst-signaled-graph-theory-discourse/)

## Cite

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

```bibtex
@inproceedings{webber2013what,
  title = {{What excludes an Alternative in Coherence Relations?}},
  author = {Webber, Bonnie},
  booktitle = {Proceedings of the 10th International Conference on Computational Semantics (IWCS 2013) – Long Papers},
  year = {2013},
  url = {https://aclanthology.org/W13-0124/}
}
```

- [← previous Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions](https://md.research.elamur.ai/free/papers/artzi-2013-weakly-supervised-learning-semantic-parsers/)
- [next → Word Segmentation, Unknown-word Resolution, and Morphological Agreement in a Hebrew Parsing System](https://md.research.elamur.ai/free/papers/cl-2013-goldberg-word-segmentation-unknown-word-resolution/)
- [↑ back to papers of 2013](https://md.research.elamur.ai/free/papers/2013/page/2/)

## References

27 references, 6 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Carlson, L. and D. Marcu (2001). Discourse tagging reference manual. Technical Report ISI-TR-545, Information Sciences Institute. [find](https://scholar.google.com/scholar?q=Carlson%2C+L%2E+and+D%2E+Marcu+%282001%29%2E+Discourse+tagging+reference+manual%2E+Technical+Report+ISI%2DTR%2D545%2C+Information+Sciences+Institute%2E)
2. Carlson, L., D. Marcu, and M. E. Okurowski (2003). Building a discourse-tagged corpus in the framework of rhetorical structure theory. In J. van Kuppevelt & R. Smith (Ed.), Current Directions in Discourse and Dialogue. New York: Kluwer. [find](https://scholar.google.com/scholar?q=Carlson%2C+L%2E%2C+D%2E+Marcu%2C+and+M%2E+E%2E+Okurowski+%282003%29%2E+Building+a+discourse%2Dtagged+corpus+in+the+framework+of+rhetorical+structure+theory%2E+In+J%2E+van+Kuppevelt+%26+R%2E+Smith+%28Ed%2E%29%2C+Current+Directions+in+Disco) [our card](https://md.research.elamur.ai/free/papers/carlson-2001-building-discourse-tagged-corpus-framework/)
3. Danescu-Niculescu-Mizil, C., L. Lee, and R. Ducott (2009). Without a ’doubt’? unsupervised discovery of downward-entailing operators. In Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Boulder, Col… [find](https://scholar.google.com/scholar?q=Danescu%2DNiculescu%2DMizil%2C+C%2E%2C+L%2E+Lee%2C+and+R%2E+Ducott+%282009%29%2E+Without+a+%E2%80%99doubt%E2%80%99%3F+unsupervised+discovery+of+downward%2Dentailing+operators%2E+In+Proceedings+of+Human+Language+Technologies%3A+The+2009+Annual+Con)
4. Feng, V. W. and G. Hirst (2012). Text-level discourse parsing with rich linguistic features. In Proc. 50th Annual Meeting of the Association for Computational Linguistics, Jeju Island, Korea, pp. 60–68. [find](https://scholar.google.com/scholar?q=Feng%2C+V%2E+W%2E+and+G%2E+Hirst+%282012%29%2E+Text%2Dlevel+discourse+parsing+with+rich+linguistic+features%2E+In+Proc%2E+50th+Annual+Meeting+of+the+Association+for+Computational+Linguistics%2C+Jeju+Island%2C+Korea%2C+pp%2E+60%E2%80%936) [our card](https://md.research.elamur.ai/free/papers/feng-2012-text-level-discourse-parsing-rich/)
5. Ghosh, S., R. Johansson, G. Riccardi, and S. Tonelli (2011). Shallow discourse parsing with conditional random fields. In Proceedings, International Joint Conference on Natural Language Processing. [find](https://scholar.google.com/scholar?q=Ghosh%2C+S%2E%2C+R%2E+Johansson%2C+G%2E+Riccardi%2C+and+S%2E+Tonelli+%282011%29%2E+Shallow+discourse+parsing+with+conditional+random+fields%2E+In+Proceedings%2C+International+Joint+Conference+on+Natural+Language+Processing%2E) [our card](https://md.research.elamur.ai/free/papers/ghosh-2011-shallow-discourse-parsing-conditional-random/)
6. Halliday, M. and R. Hasan (1976). Cohesion in English. Longman. [find](https://scholar.google.com/scholar?q=Halliday%2C+M%2E+and+R%2E+Hasan+%281976%29%2E+Cohesion+in+English%2E+Longman%2E)
7. Hernault, H., H. Prendinger, D. A. duVerle, and M. Ishizuka (2010). Hilda: A discourse parser using support vector machine classication. Dialogue and Discourse 1(3), 1–33. [find](https://scholar.google.com/scholar?q=Hernault%2C+H%2E%2C+H%2E+Prendinger%2C+D%2E+A%2E+duVerle%2C+and+M%2E+Ishizuka+%282010%29%2E+Hilda%3A+A+discourse+parser+using+support+vector+machine+classication%2E+Dialogue+and+Discourse+1%283%29%2C+1%E2%80%9333%2E)
8. Knott, A. (1996). A Data-driven Methodology for Motivating a Set of Coherence Relations. Ph. D. thesis, Department of Artificial Intelligence, University of Edinburgh. [find](https://scholar.google.com/scholar?q=Knott%2C+A%2E+%281996%29%2E+A+Data%2Ddriven+Methodology+for+Motivating+a+Set+of+Coherence+Relations%2E+Ph%2E+D%2E+thesis%2C+Department+of+Artificial+Intelligence%2C+University+of+Edinburgh%2E)
9. Knott, A., J. Oberlander, M. O’Donnell, and C. Mellish (2001). Beyond elaboration: The interaction of relations and focus in coherent text. In T. Sanders, J. Schilperoord, and W. Spooren (Eds.), Text Representation:Linguistic and psycholinguistic aspects, pp. 181–196. John Benjamins Publishing. [find](https://scholar.google.com/scholar?q=Knott%2C+A%2E%2C+J%2E+Oberlander%2C+M%2E+O%E2%80%99Donnell%2C+and+C%2E+Mellish+%282001%29%2E+Beyond+elaboration%3A+The+interaction+of+relations+and+focus+in+coherent+text%2E+In+T%2E+Sanders%2C+J%2E+Schilperoord%2C+and+W%2E+Spooren+%28Eds%2E%29%2C+Text+)
10. Knott, A. and T. Sanders (1998). The classification of coherence relations and their linguistic markers. Journal of Pragmatics 30, 135–175. [find](https://scholar.google.com/scholar?q=Knott%2C+A%2E+and+T%2E+Sanders+%281998%29%2E+The+classification+of+coherence+relations+and+their+linguistic+markers%2E+Journal+of+Pragmatics+30%2C+135%E2%80%93175%2E)
11. Lin, Z. (2012). Discourse Parsing: Inferring Discourse Structure, Modelling Coherence, and its Applications. Ph. D. thesis, National University of Singapore. [find](https://scholar.google.com/scholar?q=Lin%2C+Z%2E+%282012%29%2E+Discourse+Parsing%3A+Inferring+Discourse+Structure%2C+Modelling+Coherence%2C+and+its+Applications%2E+Ph%2E+D%2E+thesis%2C+National+University+of+Singapore%2E)
12. Lin, Z., H. T. Ng, and M.-Y. Kan (2010, November). A PDTB-styled end-to-end discourse parser. Technical report, Department of Computing, National University of Singapore. http://arxiv.org/abs/1011.0835. [↗](http://arxiv.org/abs/1011.0835)
13. Mann, W. and S. Thompson (1988). Rhetorical Structure Theory: Toward a functional theory of text organization. Text 8(3), 243–281. [find](https://scholar.google.com/scholar?q=Mann%2C+W%2E+and+S%2E+Thompson+%281988%29%2E+Rhetorical+Structure+Theory%3A+Toward+a+functional+theory+of+text+organization%2E+Text+8%283%29%2C+243%E2%80%93281%2E) [our card](https://md.research.elamur.ai/free/papers/enud-1988-mann-rhetorical-structure-theory-functional/)
14. Marcu, D. (2000). The theory and practice of discourse parsing and summarization. MIT Press. [find](https://scholar.google.com/scholar?q=Marcu%2C+D%2E+%282000%29%2E+The+theory+and+practice+of+discourse+parsing+and+summarization%2E+MIT+Press%2E)
15. Marcu, D. and A. Echihabi (2002). An unsupervised approach to recognizing discourse relations. In Proceedings of ACL’02. [find](https://scholar.google.com/scholar?q=Marcu%2C+D%2E+and+A%2E+Echihabi+%282002%29%2E+An+unsupervised+approach+to+recognizing+discourse+relations%2E+In+Proceedings+of+ACL%E2%80%9902%2E) [our card](https://md.research.elamur.ai/free/papers/marcu-2002-unsupervised-approach-recognizing-discourse-relations/)
16. Martin, J. (1992). English Text: System and Structure. Philadelphia: John Benjamins. [find](https://scholar.google.com/scholar?q=Martin%2C+J%2E+%281992%29%2E+English+Text%3A+System+and+Structure%2E+Philadelphia%3A+John+Benjamins%2E)
17. Mauri, C. (2008). Towards a typology of disjunction. Studies in Language 32, 22–55. [find](https://scholar.google.com/scholar?q=Mauri%2C+C%2E+%282008%29%2E+Towards+a+typology+of+disjunction%2E+Studies+in+Language+32%2C+22%E2%80%9355%2E)
18. Moore, J. and M. Pollack (1992). A problem for RST: The need for multi-level discouse analysis. Computational Linguistics 18(4), 537–544. [find](https://scholar.google.com/scholar?q=Moore%2C+J%2E+and+M%2E+Pollack+%281992%29%2E+A+problem+for+RST%3A+The+need+for+multi%2Dlevel+discouse+analysis%2E+Computational+Linguistics+18%284%29%2C+537%E2%80%93544%2E)
19. Palmer, F. (2001). Mood and Modality (2 ed.). Cambridge: Cambridge University Press. [find](https://scholar.google.com/scholar?q=Palmer%2C+F%2E+%282001%29%2E+Mood+and+Modality+%282+ed%2E%29%2E+Cambridge%3A+Cambridge+University+Press%2E)
20. Prasad, R., N. Dinesh, A. Lee, E. Miltsakaki, L. Robaldo, A. Joshi, and B. Webber (2008). The Penn Discourse TreeBank 2.0. In Proceedings, 6th International Conference on Language Resources and Evaluation, Marrakech, Morocco, pp. 2961–2968. [find](https://scholar.google.com/scholar?q=Prasad%2C+R%2E%2C+N%2E+Dinesh%2C+A%2E+Lee%2C+E%2E+Miltsakaki%2C+L%2E+Robaldo%2C+A%2E+Joshi%2C+and+B%2E+Webber+%282008%29%2E+The+Penn+Discourse+TreeBank+2%2E0%2E+In+Proceedings%2C+6th+International+Conference+on+Language+Resources+and+Evalua) [our card](https://md.research.elamur.ai/free/papers/disc-2008-prasad-penn-discourse-treebank-2-0/)
21. Prasad, R., S. McRoy, N. Frid, A. Joshi, and H. Yu (2011). The Biomedical Discourse Relation Bank. BMC Bioinformatics 12(188), 18 pages. [http://www.biomedcentral.com/1471-2015/12/188](http://www.biomedcentral.com/1471-2015/12/188). [↗](http://www.biomedcentral.com/1471-2015/12/188)
22. Sagae, K. (2009). Analysis of discourse structure with syntactic dependencies and data-driven shift-reduce parsing. In In Proceedings of IWPT 2009. [find](https://scholar.google.com/scholar?q=Sagae%2C+K%2E+%282009%29%2E+Analysis+of+discourse+structure+with+syntactic+dependencies+and+data%2Ddriven+shift%2Dreduce+parsing%2E+In+In+Proceedings+of+IWPT+2009%2E)
23. Sporleder, C. and A. Lascarides (2008). Using automatically labelled examples to classify rhetorical relations: an assessment. Natural Language Engineering 14(3), 369–416. [find](https://scholar.google.com/scholar?q=Sporleder%2C+C%2E+and+A%2E+Lascarides+%282008%29%2E+Using+automatically+labelled+examples+to+classify+rhetorical+relations%3A+an+assessment%2E+Natural+Language+Engineering+14%283%29%2C+369%E2%80%93416%2E)
24. Stede, M. (2012). Discourse Processing. Morgan & Claypool Publishers. [find](https://scholar.google.com/scholar?q=Stede%2C+M%2E+%282012%29%2E+Discourse+Processing%2E+Morgan+%26+Claypool+Publishers%2E)
25. Subba, R., B. D. Eugenio, and S. N. Kim (2006). Discourse parsing: Learning fol rules based on rich verb semantic representations to automatically label rhetorical relations. In Proc. EACL Workshop on Learning Structured Information in Natural Language Applications. [find](https://scholar.google.com/scholar?q=Subba%2C+R%2E%2C+B%2E+D%2E+Eugenio%2C+and+S%2E+N%2E+Kim+%282006%29%2E+Discourse+parsing%3A+Learning+fol+rules+based+on+rich+verb+semantic+representations+to+automatically+label+rhetorical+relations%2E+In+Proc%2E+EACL+Workshop+on)
26. The PDTB Research Group (2008). The Penn Discourse TreeBank 2.0 Annotation Manual. [http://www.seas.upenn.edu/˜pdtb/](http://www.seas.upenn.edu/˜pdtb/), or as part of the download of LDC2008T05. [↗](http://www.seas.upenn.edu/˜pdtb/)
27. Webber, B., M. Egg, and V. Kordoni (2012). Discourse structure and language technology. Natural Language Engineering 18(4), 437–490. [find](https://scholar.google.com/scholar?q=Webber%2C+B%2E%2C+M%2E+Egg%2C+and+V%2E+Kordoni+%282012%29%2E+Discourse+structure+and+language+technology%2E+Natural+Language+Engineering+18%284%29%2C+437%E2%80%93490%2E)
