---
title: "Computing Presuppositions by Contextual Reasoning (1999)"
description: "The paper tackles presupposition projection: deciding which presupposed facts in a discourse, such as the marriage implied by… 12 references."
authors: ["Christof Monz"]
year: 1999
venue: "In: P. Brezillon, R. Turner, J-C. Pomerol and E. Turner (Eds.) Proceedings of the AAAI-99 Workshop on Reasoning in Context for AI Applications, AAAI Press, 1999, pp. 75-79"
source: "https://arxiv.org/abs/cs/0009019"
doi: "10.48550/arxiv.cs/0009019"
arxiv: "cs/0009019"
licence: "arXiv non-exclusive distribution licence (read only, no redistribution)"
licence_url: "http://arxiv.org/licenses/nonexclusive-distrib/1.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/monz-2000-computing-presuppositions-contextual-reasoning/"
---
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# Computing Presuppositions by Contextual Reasoning

**Authors:** [Christof Monz](https://md.research.elamur.ai/free/en/authors/christof-monz/) · **Year:** 1999 · **Venue:** In: P. Brezillon, R. Turner, J-C. Pomerol and E. Turner (Eds.) Proceedings of the AAAI-99 Workshop on Reasoning in Context for AI Applications, AAAI Press, 1999, pp. 75-79 · **Licence:** [arXiv non-exclusive distribution licence (read only, no redistribution)](http://arxiv.org/licenses/nonexclusive-distrib/1.0/)

**Links:** [Publisher's page](https://arxiv.org/abs/cs/0009019) · [PDF](https://arxiv.org/pdf/cs/0009019) · [DOI 10.48550/arxiv.cs/0009019](https://doi.org/10.48550/arxiv.cs/0009019) · [arXiv cs/0009019](https://arxiv.org/abs/cs/0009019) · [OpenAlex](https://openalex.org/W2101266041)

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

## Summary
The paper tackles presupposition projection: deciding which presupposed facts in a discourse, such as the marriage implied by "Sue's husband", are already supported by their local context and which ones "escape" and must be accommodated or questioned. The naive way to compute this is to send one theorem-proving query per presupposition trigger, each with its own local context. Because those contexts usually overlap, the same premises get processed again and again. Monz keeps the classic recursive projection function from Karttunen and changes how the reasoning is encoded. Projection problems are rewritten, through a translation function τ, into a meta-language with a nestable context predicate in the style of Attardi & Simi's "ist". A labelled tableau calculus then proves all of them in a single run. Labels record a context identifier and the set of contexts reachable from it, so shared premises are expanded only once. The approach is illustrated on a small discourse and motivated by dialogue systems. Such systems need to notice when a user takes for granted something never mentioned.

## Key points
- Two formal languages are used. L_pre is first-order logic plus a binary connective "/" that marks presuppositions (after Blamey 1986). L_con is first-order logic plus the context predicate ist(Γ, ϕ), where contexts are finite sets of first-order formulas.
- Karttunen's (1974) recursive function computes projected presuppositions. A trigger does not project when its local context entails it. An auxiliary function extracts the assertive content, i.e., the formula with all presupposition markers removed.
- In the worked example, a three-sentence discourse about John's marriage, the naive method needs three separate inferences that all reuse the premise "John is married". The nested ist encoding states the same checks without repeating that premise.
- Nesting must respect accessibility. A local assumption, such as the antecedent of a conditional, may not be placed in scope of later sentences.
- Tableau nodes carry labels (i, σ), where i is the context id and σ is the set of accessible contexts. A branch closes on complementary literals in the same context or in a context accessible from the other node. The ist rule mirrors the upward direction of Buvač & Mason's (CS) rule.
- Two systems are mentioned: DORIS, as an existing implemented presupposition system, and Trindi, as an example route-planning dialogue setting.

## Interesting ideas
- Instead of running many independent entailment queries whose premises overlap, encode them as one nested structure so that shared context is processed once, a general trick for any pipeline that checks many facts against growing discourse prefixes.
- Separate a formula's assertive content from its presupposed content, and add only the assertive part to the context for later material, which keeps what a sentence claims distinct from what it assumes.
- Give every derived fact a context identifier and an explicit set of accessible contexts, so that hypothetical material (if-clauses) is visible inside its scope but never leaks outside it.
- Treat a projected presupposition, one not supported by context or the knowledge base, as a signal that the system should ask back or accommodate, rather than as an error.

## For Mova

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

- **I1** (world): Checks of whether a definite description or presupposed state is already in the text's world could reuse one incrementally built context per discourse position instead of re-deriving it for each trigger.
- **I2** (frames): Frames could store presupposed facts (from possessives, definites, "again", "stop") in a separate slot from asserted ones, so implicature and projection reasoning stay explainable.
- **I3** (world): Entities and states introduced inside conditionals, negations, or reported speech could be tagged with a scope id and an accessibility set, so they do not wrongly become facts of the main story world.
- **I4** (answer): When a test question presupposes something absent from the fable or problem text, the reader could report the gap explicitly instead of guessing, which also gives a clean negative-control case.

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

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## Cite

Cite as: Christof Monz. 1999. Computing Presuppositions by Contextual Reasoning. In: P. Brezillon, R. Turner, J-C. Pomerol and E. Turner (Eds.) Proceedings of the AAAI-99 Workshop on Reasoning in Context for AI Applications, AAAI Press, 1999, pp. 75-79.

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

```bibtex
@inproceedings{monz1999computing,
  title = {{Computing Presuppositions by Contextual Reasoning}},
  author = {Christof Monz},
  booktitle = {In: P. Brezillon, R. Turner, J-C. Pomerol and E. Turner (Eds.) Proceedings of the AAAI-99 Workshop on Reasoning in Context for AI Applications, AAAI Press, 1999, pp. 75-79},
  year = {1999},
  doi = {10.48550/arxiv.cs/0009019},
  eprint = {cs/0009019},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.48550/arxiv.cs/0009019}
}
```

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## References

12 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Attardi, G., and Simi, M. 1994a. Building proofs in context. In Proc. of Meta ’94, LNCS 883, 410–424. Springer. [find](https://scholar.google.com/scholar?q=Attardi%2C+G%2E%2C+and+Simi%2C+M%2E+1994a%2E+Building+proofs+in+context%2E+In+Proc%2E+of+Meta+%E2%80%9994%2C+LNCS+883%2C+410%E2%80%93424%2E+Springer%2E)
2. Attardi, G., and Simi, M. 1994b. Proofs in context. In Doyle, J., and Torasso, P., eds., Principles of Knowledge Representation and Reasoning: Proc. of the Fourth International Conference. Morgan Kaufmann. [↗](https://doi.org/10.1016/b978-1-4832-1452-8.50099-3)
3. Blackburn, P.; Bos, J.; Kohlhase, M.; and de Nivelle, H. 1999. Inference and computational semantics. In Bunt, H., and Thijsse, E., eds., 3rd International Workshop on Computational Semantics (IWCS-3), 5–21. Tilburg University. [find](https://scholar.google.com/scholar?q=Blackburn%2C+P%2E%3B+Bos%2C+J%2E%3B+Kohlhase%2C+M%2E%3B+and+de+Nivelle%2C+H%2E+1999%2E+Inference+and+computational+semantics%2E+In+Bunt%2C+H%2E%2C+and+Thijsse%2C+E%2E%2C+eds%2E%2C+3rd+International+Workshop+on+Computational+Semantics+%28IWCS%2D3%29)
4. Blamey, S. 1986. Partial logic. In Gabbay, D., and Guenthner, F., eds., Handbook of Philosophical Logic, volume III. Kluwer Academic Publishers. 1–70. [find](https://scholar.google.com/scholar?q=Blamey%2C+S%2E+1986%2E+Partial+logic%2E+In+Gabbay%2C+D%2E%2C+and+Guenthner%2C+F%2E%2C+eds%2E%2C+Handbook+of+Philosophical+Logic%2C+volume+III%2E+Kluwer+Academic+Publishers%2E+1%E2%80%9370%2E)
5. Buvač, S., and Mason, I. 1993. Propositional logic of context. In Fikes, R., and Lehnert, W., eds., Proceedings of the Eleventh National Conference on Artificial Intelligence, 412–419. Menlo Park, California: AAAI Press. [find](https://scholar.google.com/scholar?q=Buvac%CC%8C%2C+S%2E%2C+and+Mason%2C+I%2E+1993%2E+Propositional+logic+of+context%2E+In+Fikes%2C+R%2E%2C+and+Lehnert%2C+W%2E%2C+eds%2E%2C+Proceedings+of+the+Eleventh+National+Conference+on+Artificial+Intelligence%2C+412%E2%80%93419%2E+Menlo+Park%2C+Ca)
6. Buvač, S. 1996. Resolving lexical ambiguity using a formal theory of context. In Peters, S., and van Deemter, K., eds., Semantic Ambiguity and Underspecification. CSLI Lecture Notes. 101– 124. [find](https://scholar.google.com/scholar?q=Buvac%CC%8C%2C+S%2E+1996%2E+Resolving+lexical+ambiguity+using+a+formal+theory+of+context%2E+In+Peters%2C+S%2E%2C+and+van+Deemter%2C+K%2E%2C+eds%2E%2C+Semantic+Ambiguity+and+Underspecification%2E+CSLI+Lecture+Notes%2E+101%E2%80%93+124%2E)
7. Cooper et al., R. 1999. Coding instructional dialogue for information states. Deliverable D1.3, Trindi Project. [find](https://scholar.google.com/scholar?q=Cooper+et+al%2E%2C+R%2E+1999%2E+Coding+instructional+dialogue+for+information+states%2E+Deliverable+D1%2E3%2C+Trindi+Project%2E)
8. Karttunen, L., and Peters, S. 1979. Conventional implicatures in Montague Grammar. In Oh, C., and Dineen, D., eds., Syntax and Semantics 11: Presupposition. Academic Press, New York. 1–56. [find](https://scholar.google.com/scholar?q=Karttunen%2C+L%2E%2C+and+Peters%2C+S%2E+1979%2E+Conventional+implicatures+in+Montague+Grammar%2E+In+Oh%2C+C%2E%2C+and+Dineen%2C+D%2E%2C+eds%2E%2C+Syntax+and+Semantics+11%3A+Presupposition%2E+Academic+Press%2C+New+York%2E+1%E2%80%9356%2E)
9. Karttunen, L. 1974. Presupposition and linguistic context. Theoretical Linguistics 1(1):181–194. [↗](https://doi.org/10.1515/thli.1974.1.1-3.181)
10. Monz, C., and de Rijke, M. 1999. A tableau calculus for pronoun resolution. In Murray, N., ed., Proc. of TABLEAUX’99, LNAI. Springer. [find](https://scholar.google.com/scholar?q=Monz%2C+C%2E%2C+and+de+Rijke%2C+M%2E+1999%2E+A+tableau+calculus+for+pronoun+resolution%2E+In+Murray%2C+N%2E%2C+ed%2E%2C+Proc%2E+of+TABLEAUX%E2%80%9999%2C+LNAI%2E+Springer%2E)
11. Monz, C. 1999. Contextual inference in computational semantics. Submitted for publication. [find](https://scholar.google.com/scholar?q=Monz%2C+C%2E+1999%2E+Contextual+inference+in+computational+semantics%2E+Submitted+for+publication%2E)
12. van der Sandt, R. 1992. Presupposition projection as anaphora resolution. Journal of Semantics 9:333–377. [↗](https://doi.org/10.1093/jos/9.4.333)

*Updated 1 November 2026*