---
title: "Where Frameworks (Dis)agree: A Study of Discourse"
description: "Theoretical frameworks define DUs in quite different ways. 43 references, cited by 2 papers here."
authors: ["Maciej Ogrodniczuk", "Anna Latusek", "Karolina Saputa", "Alina Wróblewska", "Daniel Ziembicki", "Bartosz Żuk", "Martyna Lewandowska", "Adam Okrasiński", "Paulina Rosalska", "Anna Śliwicka", "Aleksandra Tomaszewska", "Sebastian Żurowski"]
year: 2025
venue: "Proceedings of the 6th Workshop on Computational Approaches to Discourse, Context and Document-Level Inferences (CODI 2025)"
source: "https://aclanthology.org/2025.codi-1.16/"
doi: "10.18653/v1/2025.codi-1.16"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/ogrodniczuk-2025-where-frameworks-dis-agree-study/"
---
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# Where Frameworks (Dis)agree: A Study of Discourse Segmentation

**Authors:** [Maciej Ogrodniczuk](https://md.research.elamur.ai/free/en/authors/maciej-ogrodniczuk/), Anna Latusek, Karolina Saputa, [Alina Wróblewska](https://md.research.elamur.ai/free/en/authors/alina-wroblewska/), [Daniel Ziembicki](https://md.research.elamur.ai/free/en/authors/daniel-ziembicki/), Bartosz Żuk, Martyna Lewandowska, Adam Okrasiński, Paulina Rosalska, Anna Śliwicka, Aleksandra Tomaszewska and Sebastian Żurowski · **Year:** 2025 · **Venue:** [Proceedings of the 6th Workshop on Computational Approaches to Discourse, Context and Document-Level Inferences (CODI 2025)](https://md.research.elamur.ai/free/en/venues/codi/) ([CODI 2025](https://md.research.elamur.ai/free/en/venues/codi/2025/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2025.codi-1.16/) · [PDF](https://aclanthology.org/2025.codi-1.16.pdf) · [DOI 10.18653/v1/2025.codi-1.16](https://doi.org/10.18653/v1/2025.codi-1.16) · [OpenAlex](https://openalex.org/W4416037857)

**Citations:** 0 citations (OpenAlex, 2026-10-14) · 2 in our library, of the 149,439 papers whose bibliographies we read

## Summary
Discourse parsing usually begins by cutting text into discourse units (DUs), and errors at this step carry into relation classification. Theoretical frameworks define DUs in quite different ways. The authors ask whether those differences actually show up in annotated English data. They first survey several formalisms, summarized in a comparison table: Hobbs' coherence theory, CCR, ISO 24617-2 and ISO 24617-8, GraphBank, PDiT 4.0, RST and PDTB. The survey asks whether units exist independently of relations, whether they may overlap or nest, whether they cover the whole text, and whether connectives belong inside them. They then build a small, interpretable segmenter of five rules over UD syntax and apply the same rules to English datasets annotated under different frameworks. A manual comparison against gold segmentation follows. The frameworks agree strongly, and clauses are the core boundaries. Disagreement concentrates on adpositional phrases, appositions, interjections and parenthesised material. The uniform rules come close to dataset-specific trained models. This suggests syntax matters for segmentation, partly contradicting Braud et al. (2017), and supports a universal, cross-framework DU definition.

## Key points
- The segmenter has five simple UD-based rules, applied identically to every tested dataset regardless of its formalism.
- The rules do not beat state-of-the-art systems, but they approach models trained separately per dataset.
- Error sources found in the manual analysis:
  - tagging and parsing mistakes inside gold data, notably in eng.dep.covdtb, such as wrong predicates, bad coordination and wrong POS;
  - inconsistent gold conventions, for example RST-style data splitting appositions only when they are in parentheses, not when set off by commas;
  - the rules over-splitting proper names, titles and compound nouns.
- Open problem areas: some subordinate clause types, parataxis, appositions and discontinuous units.
- The work comes from Universal Discourse, a project funded by the National Science Centre (Poland) that is building a model of discourse relations covering many languages and aims at cross-lingual segmentation.

## Interesting ideas
- Deriving discourse units directly from a dependency tree with a handful of clause-based rules gives a transparent segmenter that needs no training
- Running one fixed rule set against several gold sets built under different theories turns "agreement with gold" into a test of how general the rules are, not of fit to one convention
- Sorting mismatches into three bins (errors in the gold's own parse, inconsistent gold conventions, genuine mistakes of the system) prevents blaming the model for annotation noise
- Comparing frameworks along a few design questions (units independent of relations or only as arguments, overlap/nesting, full coverage, whether markers sit inside units) is a compact way to align incompatible schemes
- The observed over-splitting of names, titles and compounds shows that multiword nominal units should be protected before clause-level splitting

## For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

- **I1** (frames): prag could take clause subtrees from the UD tree as the default unit for each who-did-what-to-whom frame, keeping every frame boundary traceable to a specific dependency.
- **I2** (learn): evaluate repair rules or segmenters against multiple treebanks or annotation styles at once, and flag rules that only help one of them as convention-fitting.
- **I3** (learn): the same triage could be applied when silver data from witness parsers disagrees with a treebank, so gold errors are logged instead of trained on.
- **I4** (world): use such a checklist when merging event/relation inventories from VerbNet, FrameNet and other sources into the world model, making each source's assumptions explicit.
- **I5** (tree): treat flat/compound subtrees as atomic during any span segmentation built on gparse or perceptron parser output.

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

## Institutions

- [University of Warsaw](https://md.research.elamur.ai/free/en/universities/university-of-warsaw/) — University, Warsaw, Poland · 7 works · 496 citations
- [Polish Academy of Sciences](https://md.research.elamur.ai/free/en/government/polish-academy-of-sciences/) — Government body, Warsaw, Poland · 11 works · 520 citations
- [Institute of Computer Science](https://md.research.elamur.ai/free/en/labs/institute-of-computer-science/) — Research institute, Warsaw, Poland · 8 works · 475 citations

Also on the byline: [Nicolaus Copernicus University](https://ror.org/0102mm775).

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🧭 Topics (2): [English](https://md.research.elamur.ai/free/en/topics/english/) · 2,263 works · [🧵 Discourse analysis](https://md.research.elamur.ai/free/en/topics/discourse-analysis/) · 466 works

## Cite

Cite as: Maciej Ogrodniczuk, Anna Latusek, Karolina Saputa, Alina Wróblewska, Daniel Ziembicki, Bartosz Żuk, Martyna Lewandowska, Adam Okrasiński, Paulina Rosalska, Anna Śliwicka, Aleksandra Tomaszewska and Sebastian Żurowski. 2025. Where Frameworks (Dis)agree: A Study of Discourse Segmentation. Proceedings of the 6th Workshop on Computational Approaches to Discourse, Context and Document-Level Inferences (CODI 2025).

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

```bibtex
@inproceedings{ogrodniczuk2025where,
  title = {{Where Frameworks (Dis)agree: A Study of Discourse Segmentation}},
  author = {Maciej Ogrodniczuk, Anna Latusek, Karolina Saputa, Alina Wróblewska, Daniel Ziembicki, Bartosz Żuk, Martyna Lewandowska, Adam Okrasiński, Paulina Rosalska, Anna Śliwicka, Aleksandra Tomaszewska and Sebastian Żurowski},
  booktitle = {Proceedings of the 6th Workshop on Computational Approaches to Discourse, Context and Document-Level Inferences (CODI 2025)},
  year = {2025},
  doi = {10.18653/v1/2025.codi-1.16},
  url = {https://doi.org/10.18653/v1/2025.codi-1.16}
}
```

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## References

43 references, 17 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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*Updated 1 November 2026*