Ying et al. 2025: epistemic language as threshold semantics over credence #
[YZXW+25] ("Understanding
Epistemic Language with a Language-augmented Bayesian Theory of
Mind", TACL 13) interpret epistemic vocabulary — attitude verbs,
modal verbs, and modal adjectives — as threshold functions over agent
credence, with credence computed by Bayesian theory-of-mind inference
from observed actions. EpistemicEntry renders their lexical entries
(their Table 1): a credence threshold plus a factivity flag, with the
threshold values the paper's grid-search best fits against human
plausibility ratings in a Doors, Keys & Gems gridworld — the ordering
is the theoretical commitment, the specific values are empirical
fits. The Table 1 operator inventory (knowsIf, uncertainIf,
knowsAbout, mostSup, ...) and the scalar entailments
(knows_entails_believes, must_entails_might, ...) follow.
The bridge section connects the English modal fragment
(English.Auxiliaries) to the fitted entries: the Fragment's forms
map to entries, necessity-force modals carry strictly higher
thresholds than possibility-force modals, and the within-force scalar
ordering (must > should; may > might) captures differences binary
force cannot express. The final section records the divergence from
[HF19]'s independently fitted threshold for
probably.
The epistemic lexicon (Table 1) #
An epistemic lexical entry: the expression holds iff credence
clears θ, with factive marking the additional truth
requirement of knows. The lexical form is carried by the
Fragment (English.Auxiliaries), not the entry.
- θ : ℚ
Credence threshold.
- factive : Bool
Truth requirement at the evaluation world (knows but not believes).
Instances For
Equations
- YingEtAl2025.instDecidableEqEpistemicEntry.decEq { θ := a, factive := a_1 } { θ := b, factive := b_1 } = if h : a = b then h ▸ if h : a_1 = b_1 then h ▸ isTrue ⋯ else isFalse ⋯ else isFalse ⋯
Instances For
Equations
- YingEtAl2025.instReprEpistemicEntry = { reprPrec := YingEtAl2025.instReprEpistemicEntry.repr }
Equations
- One or more equations did not get rendered due to their size.
Instances For
The fitted thresholds (Table 1(b)):
must = certain (0.95) > should (0.80) > believes (0.75) >
likely = uncertain (0.70) > unlikely (0.40) > may (0.30) >
might = could (0.20). uncertain and unlikely are
reversed-polarity: they hold when credence is strictly below the
threshold (failsThreshold).
Equations
- YingEtAl2025.EpistemicEntry.believes = { θ := 3 / 4 }
Instances For
Equations
- YingEtAl2025.EpistemicEntry.knows = { θ := 3 / 4, factive := true }
Instances For
Equations
- YingEtAl2025.EpistemicEntry.certain = { θ := 19 / 20 }
Instances For
Equations
- YingEtAl2025.EpistemicEntry.must = { θ := 19 / 20 }
Instances For
Equations
- YingEtAl2025.EpistemicEntry.should = { θ := 4 / 5 }
Instances For
Equations
- YingEtAl2025.EpistemicEntry.likely = { θ := 7 / 10 }
Instances For
Equations
- YingEtAl2025.EpistemicEntry.may = { θ := 3 / 10 }
Instances For
Equations
- YingEtAl2025.EpistemicEntry.might = { θ := 1 / 5 }
Instances For
Equations
- YingEtAl2025.EpistemicEntry.could = { θ := 1 / 5 }
Instances For
Equations
- YingEtAl2025.EpistemicEntry.uncertain = { θ := 7 / 10 }
Instances For
Equations
- YingEtAl2025.EpistemicEntry.unlikely = { θ := 2 / 5 }
Instances For
The superlative multiplier α_most (Table 1(b)).
Equations
Instances For
The threshold scale is strictly decreasing: must = certain > should > believes > likely = uncertain > unlikely > may > might = could.
Full evaluation of an entry: credence clears the threshold, and factive entries additionally require the complement at the evaluation world.
Equations
- YingEtAl2025.holdsAt cr e a φ w = (EpistemicThreshold.meetsThreshold cr e.θ a φ ∧ (e.factive = true → w ∈ φ))
Instances For
A stronger entry — higher threshold, weaker factivity — entails a weaker one. Every pairwise entailment below is one application.
knows entails believes: same threshold, knows adds factivity.
knows is veridical: knowledge entails truth.
certain entails believes.
must entails should.
should entails likely.
must entails might: necessity entails possibility on the threshold scale.
believes entails may.
Structural operators (Table 1(a)) #
knows_if: the agent knows the answer to the polar question ?φ.
Equations
- YingEtAl2025.knowsIf cr a φ w = (YingEtAl2025.holdsAt cr YingEtAl2025.EpistemicEntry.knows a φ w ∨ YingEtAl2025.holdsAt cr YingEtAl2025.EpistemicEntry.knows a φᶜ w)
Instances For
not_knows_that: φ is true but the agent does not believe it.
Equations
- YingEtAl2025.notKnowsThat cr a φ w = (¬EpistemicThreshold.meetsThreshold cr YingEtAl2025.EpistemicEntry.believes.θ a φ ∧ w ∈ φ)
Instances For
uncertain_if: the agent's credence in both alternatives falls below the uncertain threshold.
Equations
- One or more equations did not get rendered due to their size.
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The strengthened superlative most_str: credence reaches α_most times the entry's threshold.
Equations
- YingEtAl2025.mostStr cr e a φ = (YingEtAl2025.EpistemicEntry.α_most * e.θ ≤ cr a φ)
Instances For
Quantified operators (Table 1(a)) #
knows_about, certain_about, uncertain_about, and most_sup quantify over a context-restricted entity domain, for sentences like "the player knows which box has the key".
knows_about: for some contextually relevant entity, the agent knows that φ holds of it.
Equations
- YingEtAl2025.knowsAbout cr a C φ w = ∃ (x : X), C x ∧ YingEtAl2025.holdsAt cr YingEtAl2025.EpistemicEntry.knows a (φ x) w
Instances For
certain_about: for some contextually relevant entity, credence in φ of it clears the certain threshold.
Equations
- YingEtAl2025.certainAbout cr a C φ = ∃ (x : X), C x ∧ EpistemicThreshold.meetsThreshold cr YingEtAl2025.EpistemicEntry.certain.θ a (φ x)
Instances For
uncertain_about: for every contextually relevant entity, credence
falls below the uncertain threshold — the universal dual of
certainAbout's existential.
Equations
- YingEtAl2025.uncertainAbout cr a C φ = ∀ (x : X), C x → EpistemicThreshold.failsThreshold cr YingEtAl2025.EpistemicEntry.uncertain.θ a (φ x)
Instances For
most_sup: credence in φ of the object is at least credence in φ of every contextually relevant alternative.
Equations
- YingEtAl2025.mostSup cr a o C φ = ∀ (x : X), C x → cr a (φ x) ≤ cr a (φ o)
Instances For
A known witness gives knows_about.
certain_about supplies a believed witness.
uncertain_about and certain_about are incompatible.
Fragment bridge: English modal auxiliaries #
Map an English modal auxiliary to its epistemic threshold entry;
non-epistemic modals (deontic shall) have none. The mapping
derives from the Fragment's form field.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The epistemic force of a modal auxiliary, if it has an epistemic reading.
Equations
- One or more equations did not get rendered due to their size.
Instances For
Per-entry checks of the form → entry → threshold pipeline; these break if the Fragment's form field or the fitted threshold changes.
Non-epistemic modals have no threshold entry.
Force–threshold consistency #
Necessity-force epistemic modals carry strictly higher thresholds than possibility-force ones — [Kra81]'s algebraic force and the fitted thresholds characterize the same items consistently.
The epistemic force of must is necessity (from the Fragment).
The epistemic force of might is possibility.
The epistemic force of should is weak necessity.
The epistemic force of may is possibility.
Within-force ordering #
The □ > □w gap (must > should) is expressible by the three-way
ModalForce; the within-◇ gap (may > might) remains a purely scalar
difference.
Strong necessity must outranks weak necessity should.
Among possibility modals, may outranks might.
might and could share a threshold.
Divergence from Herbstritt & Franke 2019 #
[HF19] (Cognition 186) independently infer a credence threshold for probably by Bayesian fitting against urn-production data, reporting a posterior mean of 0.549 with 95% HDI [0.500, 0.594] (their Table 6). The fitted threshold for likely here (0.70) lies above that interval's upper bound, so the two parameter-fitted accounts disagree at the 95%-credibility level. Candidate explanations: lexical (probably ≠ likely), task (urn production vs. theory-of-mind in a gridworld), or posterior uncertainty (points vs. intervals).
The fitted likely threshold exceeds the upper bound of [HF19]'s 95% HDI for probably (their Table 6).