---
title: "Using Structural Constraints for Speech Act Interpretation (1989)"
description: "The authors argue this approach cannot capture phrasing subtleties. 4 references. Among them: 3."
authors: ["James F. Allen", "Elizabeth Hinkelman"]
year: 1989
venue: "Speech and Natural Language: Proceedings of a Workshop Held at Cape Cod, Massachusetts, October 15-18, 1989"
source: "https://aclanthology.org/H89-2052/"
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/allen-1989-structural-constraints-speech-act-interpretation/"
---
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# Using Structural Constraints for Speech Act Interpretation

**Authors:** [James F. Allen](https://md.research.elamur.ai/free/en/authors/james-f-allen/) and [Elizabeth Hinkelman](https://md.research.elamur.ai/free/en/authors/elizabeth-hinkelman/) · **Year:** 1989 · **Venue:** [Speech and Natural Language: Proceedings of a Workshop Held at Cape Cod, Massachusetts, October 15-18, 1989](https://md.research.elamur.ai/free/en/venues/darpa-workshop-on-speech-and-natural-language-hlt/) ([HLT 1989](https://md.research.elamur.ai/free/en/venues/darpa-workshop-on-speech-and-natural-language-hlt/1989/)) · **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/H89-2052/) · [PDF](https://aclanthology.org/H89-2052.pdf) · [OpenAlex](https://openalex.org/W2119478981)

**Citations:** 3 citations (OpenAlex, 2026-10-14)

## Summary
Allen and Hinkelman challenge the literal meaning hypothesis. That hypothesis holds that sentence structure fixes one context-free "literal" speech act, and that any indirect meaning is reached later by plan reasoning from that starting point. The authors argue this approach cannot capture phrasing subtleties. For example, *Can you pass the salt* works as a request, while a paraphrase that explicitly asks the hearer to report on their ability to pass the salt is only a question about ability. The approach also cannot absorb cues like intonation, and it wastes effort re-deriving common indirect forms from first principles. In their alternative, structural interpretation rules match a combined syntactic structure and logical form. The rules output an interpretation space with two parts: limits on what the intended act may be, and specific conventional readings it is likely to be. A plan reasoner then filters these candidates against act constraints, preconditions and effects. Only when ambiguity remains does it fall back on general plan recognition based on Kautz's algorithm. A prototype built in COMMONLISP within RHET runs all the paper's examples. The authors claim it is faster on conventional forms, more accurate, and open to prosodic input. They report no quantitative evaluation.

## Key points
- The paper targets the literal meaning hypothesis used by Searle and by earlier Allen & Perrault work, where syntactic mood mapped to a surface act:
  - imperative → surface request,
  - declarative → surface inform,
  - interrogative → request to inform.
- It relies on Searle's five act classes: Representatives, Directives, Commissives, Expressives, and Declaratives.
- Older systems compiled shortcuts such as REQUEST decomposing into SURFACE-REQUEST(INFORMIF(CANDO)). These shortcuts still began from literal meaning, so they could not tell paraphrases apart.
- A sample "can you" rule fires on a yes/no question with auxiliary *can*, subject *you* and an action verb. It yields two items: {REQUEST of that action, generic SPEECHACT}. If filtering leaves one specific reading, the system accepts it.
- The implementation uses COMMONLISP and the RHET environment, with plan recognition following Kautz. The prototype covers only a limited knowledge base of acts and rules.

## Interesting ideas
- Have the structural stage emit a bounded set of candidate readings plus a coarse class constraint, rather than one committed meaning, and let context prune that set. This keeps cheap structure-driven guesses while leaving room for reasoning.
- Encode conventional indirect forms as pattern rules over parse plus logical form, keyed on specific features like auxiliary, subject person, mood and verb type. This makes "Can you X?" and "Tell me whether you can X" diverge naturally.
- Filter candidate acts by testing their constraints, preconditions and effects against context, and run full plan inference only when filtering leaves ambiguity. This gives a fast path for common cases and an expensive path for hard ones.
- Treat every cue source, including punctuation and (in speech) intonation, as just another rule family that restricts the same interpretation space. New evidence then plugs in without redesign.
- The authors suggest attaching frequency weights to interpretation rules but warn that the weights are hard to set, since "can you" sentences have many genuine yes/no uses (e.g. eating three pizzas in ten minutes).

## For Mova

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

- **I1** (frames): prag could output a speech-act space per clause (e.g. {request(lift rock), any-act}) derived from the UD tree, then narrow it with world-of-text checks.
- **I2** (frames): match UD features (aux lemma *can*, nsubj *you*, Mood=Int) to propose request frames, keeping each rule as an explainable trace.
- **I3** (world): check whether the addressee is the agent and whether the action is feasible in the text's world before keeping a directive reading.
- **I4** (frames): a final "?" on a declarative ("You are going to the party?") could add a question candidate through the same mechanism.
- **I5** (learn): estimate rule weights from silver data and test them on negative controls such as genuine ability questions.

*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 Rochester](https://md.research.elamur.ai/free/en/universities/university-of-rochester/) — University, Rochester, United States · 36 works · 7,398 citations

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🧭 Topics (1): [💬 Speech act theory](https://md.research.elamur.ai/free/en/topics/speech-act-theory/) · 229 works

## Cite

Cite as: James F. Allen and Elizabeth Hinkelman. 1989. Using Structural Constraints for Speech Act Interpretation. Speech and Natural Language: Proceedings of a Workshop Held at Cape Cod, Massachusetts, October 15-18, 1989.

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

```bibtex
@inproceedings{allen1989using,
  title = {{Using Structural Constraints for Speech Act Interpretation}},
  author = {James F. Allen and Elizabeth Hinkelman},
  booktitle = {Speech and Natural Language: Proceedings of a Workshop Held at Cape Cod, Massachusetts, October 15-18, 1989},
  year = {1989},
  doi = {10.3115/1075434.1075497},
  url = {https://doi.org/10.3115/1075434.1075497}
}
```

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## References

4 references, 1 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Allen, J.F., "Recognizing intentions from natural language utterances," in M. Brady and R.C. Berwick (eds.), Computational Models of Discourse. Cambridge, MA: MIT Press, 107-166, 1983. [find](https://scholar.google.com/scholar?q=Allen%2C+J%2EF%2E%2C+%22Recognizing+intentions+from+natural+language+utterances%2C%22+in+M%2E+Brady+and+R%2EC%2E+Berwick+%28eds%2E%29%2C+Computational+Models+of+Discourse%2E+Cambridge%2C+MA%3A+MIT+Press%2C+107%2D166%2C+1983%2E)
2. Allen, J.F., Natural Language Understanding, Benjamin Cummings Publishing Co., 1987. Allen, J.F. and C.R. Perrault, "A plan-based analysis of indirect speech acts," American Journal of Computational Linguistics 3, 167-182, 1981. Allen, J.F. and B.W. Miller, "The Rhetorical knowledge representation system: A user's manual (for Rhet version 14.45)," TR 238, Computer Science Dept., U. Rochester, revised March 1989. Austin, J.L., "How to Do Things with Words," New York: Oxford U. Press, 1962. Carberry, S., "Tracking user goals in an information-seeking environment," Proc., AAAI, 59-63, 1983. Fikes, R.E. and N.J. Nilsson, "STRIPS: A new approach to the application of theorem proving to problem solving," Artificial Intelligence 2, 3/4, 189-208, 1971. Gfice, H.P., "Meaning," Philosophical Review 66, 377-388, 1957; reprinted in D. Steinburg and L. Jakobovits (eds.). Semantics. New York: Cambridge U. Press, 1971. Hinkelman, E.A., "Linguistic and pragmatic constraints on utterance interpretation," Ph.D. [find](https://scholar.google.com/scholar?q=Allen%2C+J%2EF%2E%2C+Natural+Language+Understanding%2C+Benjamin+Cummings+Publishing+Co%2E%2C+1987%2E+Allen%2C+J%2EF%2E+and+C%2ER%2E+Perrault%2C+%22A+plan%2Dbased+analysis+of+indirect+speech+acts%2C%22+American+Journal+of+Computational+L)
3. Thesis, Computer Science Dept., U. Rochester, 1989. Hinkelman, E.A. and J.F. Allen, "[Two constraints on speech act ambiguity](https://md.research.elamur.ai/free/en/papers/hinkelman-1989-two-constraints-speech-act-ambiguity/)," Proc., Association for Computational Linguistics, 212-219, 1989. Kautz, H.A., "A formal theory of plan recognition," Ph.D. Thesis and TR 215, Computer Science Dept., U.
4. Rochester, 1987. Kautz, H.A. and J.F. Allen, "Generalized plan recognition," Proc., AAAI Nat'l. Conf. on Artificial Intelligence, 1986. Litman, DJ. and J.F. Alien, "A plan recognition model for subdialogues in conversations," Cognitive Science 11, 2, 163-200, 1987. Perrault, C.R. and J.F. Allen, "A plan-based analysis of indirect speech acts," AJCL 6, 3-4, 167-182, 1980. Searle, J.R., in Speech Acts, Cambridge University Press, New York, 1969. Searle, J.R., "Indirect speech acts," in P. Cole and J. Morgan (eds.). Syntax and Semantics 3: Speech Acts. New York: Academic Press, 59-82, 1975a. Searle, J.R., "A taxonomy of illocutionary acts," in K. (ed), Language, Mind and Knowledge, Univ. of Minnesota Press, 1975b. Sidner, C.L. and Israel, D.J., "Recognizing Intended Meaning and Speakers' Plans," Proc. IJCAI "81,203-208, 1981. Tenenberg, J.D., "Abstraction in planning," Ph.D. Thesis and TR 250, Computer Science Dept., U. Rochester, 1988. 8. SUMMARY [find](https://scholar.google.com/scholar?q=Rochester%2C+1987%2E+Kautz%2C+H%2EA%2E+and+J%2EF%2E+Allen%2C+%22Generalized+plan+recognition%2C%22+Proc%2E%2C+AAAI+Nat%27l%2E+Conf%2E+on+Artificial+Intelligence%2C+1986%2E+Litman%2C+DJ%2E+and+J%2EF%2E+Alien%2C+%22A+plan+recognition+model+for+subdia)

*Updated 29 October 2026*