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# Unpacking Ambiguity: The Interaction of Polysemous Discourse Markers and Non-DM Signals

**Authors:** Jingni Wu, [Amir Zeldes](https://md.mova.elamur.ai/free/en/docs/papers/authors/amir-zeldes/) · **Year:** 2025 · **Venue:** CODI 2025 **Link:** [aclanthology.org/2025.codi-1.2](https://aclanthology.org/2025.codi-1.2/) · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

[**0** citations](https://openalex.org/works?filter=cites:W4416037881) openalex-snapshot · 2026-10-14[Proceedings of the 6th Workshop on Computational Approaches to Discourse, Context and Document-Level Inferences (CODI 2025)](https://aclanthology.org/volumes/2025.codi-1/)[licence](https://creativecommons.org/licenses/by/4.0/)

- [Publisher's page](https://aclanthology.org/2025.codi-1.2/)
- [PDF](https://aclanthology.org/2025.codi-1.2.pdf)
- [DOI 10.18653/v1/2025.codi-1.2](https://doi.org/10.18653/v1/2025.codi-1.2)
- [arXiv 2507.16748](https://arxiv.org/abs/2507.16748)
- [OpenAlex](https://openalex.org/W4416037881)

**Authors (2)**

1. [Jingni Wu](https://openalex.org/A5067195997) h 1 · 2 citations · 12 works
2. [Amir Zeldes](https://openalex.org/A5089212858) [ORCID](https://orcid.org/0000-0001-8016-6753) · h 16 · 1524 citations · 238 works

Citations and author metrics from openalex-snapshot (2026-10-14); authors with the same name are not always told apart.

## What it is about

Using GUM's eRST layer (16 genres, over 250K tokens, discourse markers plus seven types of non-marker signals: graphical, lexical, morphological, numerical, reference, semantic, syntactic), the paper measures how ambiguous each discourse marker is — the entropy of the relations it signals — and asks whether ambiguous markers come with more, or more varied, other signals. Overall *so* is the most polysemous marker; *and* is the most polysemous in six genres, *so* and *as* second in eight; *for, and, if, by, when* co-occur with the most diverse signals. Polysemy correlates with the diversity rather than the number of accompanying signals, and genre matters a lot: spoken genres (court, podcast, vlog) lean most on extra signals, and all 16 genres differ significantly from the overall signal distribution. The most frequent combination with *and* is reference + semantic (a shared referent plus related words across the two units); in letters *as* mostly signals manner and needs no extra signal.

## Ideas

- I1. Compute the same entropy from Mova's own output: for each connective the reader handles, the distribution of link types it produced (or of teacher labels on the frame bench). High-entropy connectives (*and, so, as, since, while, when*) are where disambiguation rules pay off; low-entropy ones can stay single rules. A small report in `prag/src/fbench.rs`, recomputed per genre (tales, lessons, dialogue).
- I2. For ambiguous connectives, require a second signal of the kind the paper finds, each named in the explanation: *and* + shared referent → `next` (otherwise additive, no link); *since* + perfect tense or a time expression → temporal, else `cause`; *as* + a manner verb or *as if* → manner, + progressive/simultaneous action → temporal, else `cause`; *while* + contrasting subjects or antonyms → contrast, else temporal. Implement as tests in `prag/src/frames.rs` with `PRAG_OFF` switches; measure frame bench cause/next precision.
- I3. Keep genre as an input to these defaults (see `scholman-2022-discogem-crowdsourced-corpus-genre-mixed` I3); the paper shows the same marker shifts sense with genre (*so*, *while*, *given*, *indeed*).

## For Mova

[36. Discourse relations and coherence](https://md.mova.elamur.ai/free/en/docs/languages/en/36-discourse-relations/) §6, §11.1, §11.6 (connective senses not disambiguated). Code: `prag/src/frames.rs` (second-signal tests), `prag/src/fbench.rs` (entropy report). Measures: frame bench cause/next precision per connective and per genre.

Topics: [Discourse analysis](https://md.mova.elamur.ai/free/en/docs/papers/topics/discourse-analysis/) · [Word sense disambiguation](https://md.mova.elamur.ai/free/en/docs/papers/topics/word-sense-disambiguation/)

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.18653/v1/2025.codi-1.2](https://doi.org/10.18653/v1/2025.codi-1.2) · [arXiv 2507.16748](https://arxiv.org/abs/2507.16748)

```
@inproceedings{wu2025unpacking,
  title = {{Unpacking Ambiguity: The Interaction of Polysemous Discourse Markers and Non-DM Signals}},
  author = {Wu, Jingni and Zeldes, Amir},
  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-1.2},
  eprint = {2507.16748},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.18653/v1/2025.codi-1.2}
}
```

- [← previous QUDeval: The Evaluation of Questions Under Discussion Discourse Parsing](https://md.mova.elamur.ai/free/en/docs/papers/wu-2023-qudeval-evaluation-questions-under-discussion/)
- [next → Incremental Neural Coreference Resolution in Constant Memory](https://md.mova.elamur.ai/free/en/docs/papers/xia-2020-incremental-neural-coreference-resolution-constant/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

## References

28 references, 9 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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28. Amir Zeldes and Yang Janet Liu. 2020. A neural approach to discourse relation signal detection. Dialogue and Discourse, 11(2):74–99. Text type Source Academic writing Biographies CC Vlogs Conversations Courtroom transcripts Essays Fiction Forum How–to guides Interviews Letters News stories Podcasts Political speeches Textbooks Travel guides Various Wikipedia YouTube UCSB Corpus Various Various Various reddit wikiHow Wikinews Various Wikinews Various Various OpenStax Wikivoyage Total GUM Docs Tokens 18 20 15 15 9 9 19 18 19 19 12 24 10 15 15 18 17,169 18,213 16,864 17,932 11,148 10,842 17,511 16,364 17,081 18,196 9,989 17,186 11,986 16,720 16,693 16,515 250,409 *Table 6: Overview of GUM corpus by text type.* [↗](https://doi.org/10.5087/dad.2020.201)