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# Reasoning Requirements for Indirect Speech Act Interpretation

**Authors:** [Vasanth Sarathy](https://md.mova.elamur.ai/free/en/docs/papers/authors/vasanth-sarathy/), [Alexander Tsuetaki](https://md.mova.elamur.ai/free/en/docs/papers/authors/alexander-tsuetaki/), [Antonio Roque](https://md.mova.elamur.ai/free/en/docs/papers/authors/antonio-roque/), [Matthias Scheutz](https://md.mova.elamur.ai/free/en/docs/papers/authors/matthias-scheutz/) · **Year:** 2020 · **Venue:** COLING 2020 **Link:** [aclanthology.org/2020.coling-main.433](https://aclanthology.org/2020.coling-main.433/) · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

[**5** citations](https://openalex.org/works?filter=cites:W3114015485) openalex · 2026-10-18[Proceedings of the 28th International Conference on Computational Linguistics](https://aclanthology.org/volumes/2020.coling-main/)[licence](https://creativecommons.org/licenses/by/4.0/)

- [Publisher's page](https://aclanthology.org/2020.coling-main.433/)
- [PDF](https://aclanthology.org/2020.coling-main.433.pdf)
- [DOI 10.18653/v1/2020.coling-main.433](https://doi.org/10.18653/v1/2020.coling-main.433)
- [OpenAlex](https://openalex.org/W3114015485)

**Authors (4)**

1. [Vasanth Sarathy](https://openalex.org/A5071988241) [ORCID](https://orcid.org/0000-0003-4129-6429) · h 9 · 291 citations · 52 works
2. [Alexander Tsuetaki](https://openalex.org/A5072749905) h 2 · 9 citations · 3 works
3. Antonio Roque
4. [Matthias Scheutz](https://openalex.org/A5044523801) [ORCID](https://orcid.org/0000-0002-0064-2789) · h 55 · 10109 citations · 576 works

Citations and author metrics from openalex (2026-10-18); authors with the same name are not always told apart.

## What it is about

From three task dialogue corpora (SCARE, Diorama, Minecraft; 15,000+ utterances) the authors found only 20 pairs of near-identical questions that were an indirect request in one context and a plain question in the other. From them they build a logic model in Answer Set Programming. After Brown (1980), reading «Can you do A?» as a request needs four preconditions: the speaker wants the hearer to do A, believes the hearer capable, willing, and obliged. Surface form sets the default (question → ask, command → request, statement → assert), and the burden of proof is asymmetric: the direct reading holds unless there is evidence against it; the indirect one needs positive evidence. Evidence comes from task requirements, roles (leader/follower → delegation), interaction history (earlier requests that were carried out) and co-presence (seen capable), with event-calculus inertia (a fluent holds until terminated) and Clark's mutual-knowledge heuristic. There is no quantitative evaluation; the contribution is the axioms and a worked dialogue.

## Ideas

- I1. Take the precondition check out of the dialogue layer (`world/src/talk.rs` already has it on cue words) and into reading tales. For a quoted «Can/Could/Will you X?» in a Say frame, look in the earlier frames of the same discourse for: the speaker wanting X or its result (want/wish/need frames), the addressee having done or being able to do X, a role pair (king/servant, mother/child from nouns and vocatives). Promote to `request` only with positive evidence, and print the evidence. Measure `indirect` and request F1 on the tale part of the silver against the current perceptron.
- I2. Use uptake as a free label: if the next frames show the addressee doing the asked verb (the paper's «responsive» action), the question was taken as a request; if the addressee answers yes/no in speech, it was taken as a question. Collect these from the tale corpus as silver-free training pairs for `indirect`, and measure how far they agree with the Opus silver before using them.
- I3. Encode the asymmetric burden of proof in the agreer (`prag/src/agree.rs`): the direct act for the form is the default, and the indirect act may override it only when a named cue or precondition fires. Run it as a rule next to the three models and report its precision on `indirect=1` (high precision, low recall is the expected shape).
- I4. Add the better-knowledge cue: *can you* questions doubt capability, *will/would you* questions doubt willingness. A feature slot «modal of the inverted auxiliary» already exists in spirit (`modal`, `inv`). Check in the silver whether *will/would you* lines are requests more often than *can you* lines before adding a rule.
- I5. Event-calculus inertia for frames: a state frame («the door was locked») holds until a later frame terminates it («he unlocked it»). This is the rule that lets the reader answer «Was the door open when…?» in school questions. Use it as a small `world` reader rule and measure it with `world knowledge diagnose` on state questions.

## For Mova

[31. Speech acts](https://md.mova.elamur.ai/free/en/docs/languages/en/31-speech-acts/) §5.4 (Mova's indirect requests) and §10 (indirectness is labelled, not inferred), `38-dialogue-and-discourse-markers.md` §2 (recruitments). Code: `world/src/talk.rs` (existing precondition reasoning), `prag/src/frames.rs` and `prag/src/agree.rs` (tale reading, default rule), `prag/src/feats.rs`. Measures: `indirect` macro-F1 and request recall in `prag eval`, agreement of uptake labels with the silver, `world knowledge diagnose` for state questions.

Topics: [Speech act theory](https://md.mova.elamur.ai/free/en/docs/papers/topics/speech-act-theory/)

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.18653/v1/2020.coling-main.433](https://doi.org/10.18653/v1/2020.coling-main.433)

```
@inproceedings{sarathy2020reasoning,
  title = {{Reasoning Requirements for Indirect Speech Act Interpretation}},
  author = {Sarathy, Vasanth and Tsuetaki, Alexander and Roque, Antonio and Scheutz, Matthias},
  booktitle = {Proceedings of the 28th International Conference on Computational Linguistics},
  year = {2020},
  doi = {10.18653/v1/2020.coling-main.433},
  url = {https://doi.org/10.18653/v1/2020.coling-main.433}
}
```

- [← previous Probability and implicatures: A unified account of the scalar effects of disjunction under modals](https://md.mova.elamur.ai/free/en/docs/papers/santorio-2017-probability-implicatures-unified-account-scalar/)
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- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

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