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Quantity implicatures, exhaustive interpretation, and rational conversation

Paper · 2011 · Michael Franke

Summary

The paper asks whether quantity implicatures can be derived in a strictly Gricean way, as the outcome of rational behaviour between speaker and hearer. An example is reading "some" as "not all". Franke proposes the iterated best response (ibr) model, which has two parts. The first is a fixed recipe that turns a target utterance and its alternatives into a signaling game. In that game, states group together worlds that agree on the truth of every alternative. The speaker knows the actual state, and both players want the hearer to identify it. The second part is a solution concept. Starting from literal truth, the players take turns computing best responses to each other's previous behaviour until the process stabilises. This picks out one intuitively correct outcome, where classical equilibrium notions allow many. A simple algorithm lets readers compute the result without working through expected-utility calculations. The model covers several epistemic kinds of quantity implicature, free choice readings of disjunction under existential modals, and simplification of disjunctive antecedents. It also improves on exhaustivity-based theories while giving them a rational foundation. The result matters because it links formal pragmatics back to Grice's idea of conversation as rational action.

Key points

  • The paper is published in Semantics & Pragmatics, vol. 4, article 1 (82 pages, 2011). Its model is called ibr (iterated best response).
  • It separates four strengths of quantity inference:
    • the general epistemic one (¬Bel_S "all"),
    • the strong epistemic one (Bel_S ¬"all"),
    • the weak epistemic one (speaker uncertain about "all"),
    • the base-level one (¬"all").
  • Theorem 3: in finite games of pure cooperation (U_S = U_R), every ibr sequence reaches a fixed point. The proof shows that expected gain never decreases along the sequence.
  • Theorem 4: under two conditions on interpretation games (C1, C2), any ibr fixed point gives rise to a perfect Bayesian equilibrium. Messages the hearer does not expect ("surprise messages") are interpreted with a uniform posterior over their literal meaning.
  • The model is close to, though not generally equivalent to, iterated exhaustive interpretation. Simple implicatures follow from rational interpretation of literal meaning alone, without needing a speaker quantity maxim.

Interesting ideas

  • I1. The context is built automatically from the alternatives, with no hand-chosen states: each state is the set of worlds that give all alternative utterances the same truth values. This keeps the model falsifiable and mechanical.
  • I2. Pragmatic reasoning is grounded in literal semantics and then refined step by step. Each player responds optimally to the other's previous strategy, which makes every inference step inspectable.
  • I3. The paper gives a fallback for unexpected input: a message nobody would send under the current strategy reverts to its literal meaning, with no preference among its states. This avoids inventing interpretations.
  • I4. A monotonicity argument guarantees termination: shared payoff can only rise along the iteration, and the game is finite, so the procedure must stop.
  • I5. The paper distinguishes how strong an inference is: the speaker not believing X, the speaker believing not-X, or not-X being true. This avoids collapsing different conclusions into one.

For Mova

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

  • I1 (frames): crate prag could build its implicature candidate space from the truth-value patterns of a sentence's scale-mates (some/all, or/and), so that every derived implicature traces back to an explicit table.
  • I2 (frames): implicature in prag can be modelled as a few explicit rounds of hearer and speaker tables over UD-derived literal meanings. Each round would be logged as part of the explanation.
  • I3 (world): when a sentence fits no expected pattern, the world builder should store only its literal content, without enriching it, and mark it as uncertain.
  • I4 (learn): self-play and repair-rule loops could carry a similar monotone objective, which would give a provable stopping condition and a sanity check.
  • I5 (answer): QA over fables could label answers derived from implicature with their epistemic strength, keeping "the narrator does not claim all" separate from "not all".

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

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Computer Science · 9,085 worksArtificial Intelligence · 8,888 worksArts and Humanities · 9,296 worksLanguage and Linguistics · 9,206 works

🧭 Topics 1Research subjects and languages the work is about.Implicature · 72 works

Cite

Cite as Michael Franke. 2011. Quantity implicatures, exhaustive interpretation, and rational conversation. Semantics and Pragmatics.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.3765/sp.4.1

@article{franke2011quantity,
  title = {{Quantity implicatures, exhaustive interpretation, and rational conversation}},
  author = {Michael Franke},
  journal = {Semantics and Pragmatics},
  year = {2011},
  doi = {10.3765/sp.4.1},
  url = {https://doi.org/10.3765/sp.4.1}
}

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