Degree Semantics: Positive-Form Semantics #
Positive-form semantic operations on the types declared in Defs.lean,
plus threshold-comparison predicates on the concrete Degree max /
Threshold max carriers @cite{kennedy-2007} @cite{heim-2001}
@cite{kennedy-mcnally-2005}. Kennedy 2007's interpretive economy lives
in the sibling Kennedy.lean.
Main definitions #
positiveSem— abstract positive-form predicateμ(x) ≥ θpositiveMeaning,negativeMeaning,antonymMeaning— concrete threshold-comparison predicates onDegree max/Threshold max
Main theorems #
positiveMeaning_monotone— monotonicity in the threshold
Relationship to Gradability.Basic #
This module uses abstract types (Entity D : Type* with LinearOrder D)
for framework-level theorems. Gradability.Basic uses concrete
Degree max := Fin (max + 1) for computation in RSA models and Fragment
entries. The two serve different clients: this module is imported by
Degree/Comparative.lean and other framework siblings; Gradability.Basic
is imported by Fragments/English/ and Phenomena/Gradability/ bridges.
The positive (unmarked) form of a gradable adjective:
"Kim is tall" is true iff μ(Kim) ≥ θ for a contextual standard θ.
This is the common core across Kennedy and Heim:
- Kennedy:
⟦tall⟧ = λd.λx. height(x) ≥ d, withθ = pos(tall) - Heim:
⟦tall⟧ = λx. height(x) ≥ θ_c
Klein's approach is different: "tall" is true relative to a comparison class, with no degree parameter.
Equations
- Semantics.Degree.positiveSem μ θ x = (μ x ≥ θ)
Instances For
Concrete threshold-based meanings #
Threshold-comparison predicates on the concrete Degree max /
Threshold max carriers. These are general degree operations, not
adjective-specific. Decidability is inherited from the underlying
Degree/Threshold order.
Positive form: t < d.
Equations
- Semantics.Degree.positiveMeaning d t = ({ value := t.value.castSucc } < d)
Instances For
Negative form: d < t.
Equations
- Semantics.Degree.negativeMeaning d t = (d < { value := t.value.castSucc })
Instances For
Antonym: d ≤ t.
Equations
- Semantics.Degree.antonymMeaning d t = (d ≤ { value := t.value.castSucc })
Instances For
Monotonicity of positiveMeaning in the threshold: a higher threshold
is informationally stronger. If d > θ_strong and θ_weak ≤ θ_strong,
then d > θ_weak. Grounds the weak-vs-strong-adjective distinction
(InformationalStrength).