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Linglib.Theories.Semantics.Lexical.Adjective.Theory

@[reducible, inline]

Antonymy type: contradictory (no gap) vs contrary (gap). Canonical definition in Core.PropertyDomain.

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    A threshold pair for contrary antonyms.

    For contrary pairs like happy/unhappy:

    • theta_pos: threshold for positive form (degree > theta_pos -> "happy")
    • theta_neg: threshold for negative form (degree < theta_neg -> "unhappy")
    • Constraint: theta_neg <= theta_pos (gap exists when theta_neg < theta_pos)
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        @[reducible, inline]

        Contradictory negation: "not happy" = degree ≤ theta. Alias for Semantics.Degree.antonymMeaning — same comparison, named for its role in the contradictory/contrary distinction.

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          Contrary negation: "unhappy" = degree < theta_neg.

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            Check if a degree is in the gap region (neither positive nor negative).

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              Positive meaning with two-threshold model: degree > theta_pos.

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                Negative meaning with contrary semantics: "unhappy" = degree < theta_neg.

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                  Negation of contrary negative: "not unhappy" = degree >= theta_neg.

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                    @[reducible, inline]

                    The relation between a positive form and its antonym.

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                      Informational strength of a gradable adjective within its scale.

                      Weak adjectives (e.g., "large", "clean") occupy a broader region of the scale. Strong adjectives (e.g., "gigantic", "pristine") occupy a narrower, more extreme region.

                      A strong adjective entails its weak counterpart on the same pole: "x is gigantic" ⟹ "x is large", but not vice versa.

                      This distinction is orthogonal to scale structure (relative vs absolute) and polarity (positive vs negative).

                      Source: @cite{alexandropoulou-gotzner-2024}, @cite{horn-1972}

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                          Spatial configuration type for adjectives in resultative constructions (@cite{levin-2026}). Only adjectives describing spatially instantiated states license intr-push open resultatives.

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                              A gradable adjective lexical entry. Bundles surface form, scale structure, and antonym information. The actual threshold is NOT part of the lexical entry — it's contextual.

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                                  How a multidimensional adjective binds its dimensions (@cite{sassoon-2013}).

                                  • conjunctive: entity must meet standard in ALL dimensions (e.g., healthy)
                                  • disjunctive: entity must meet standard in SOME dimension (e.g., sick)
                                  • mixed: context determines ∀ vs ∃ (e.g., intelligent)
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                                      def Semantics.Lexical.Adjective.conjunctiveBinding {α : Type} (dims : List (αBool)) (x : α) :

                                      Conjunctive binding: ∀Q ∈ DIM(P,c). Q(x).

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                                        def Semantics.Lexical.Adjective.disjunctiveBinding {α : Type} (dims : List (αBool)) (x : α) :

                                        Disjunctive binding: ∃Q ∈ DIM(P,c). Q(x).

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                                          theorem Semantics.Lexical.Adjective.deMorgan_conjunctive_disjunctive {α : Type} (dims : List (αBool)) (x : α) :
                                          (!conjunctiveBinding dims x) = disjunctiveBinding (List.map (fun (d : αBool) (a : α) => !d a) dims) x

                                          De Morgan: negating conjunctive binding yields disjunctive binding over negated dimension predicates. This is the formal core of @cite{sassoon-2013}'s Hypothesis 2 — under a negation theory of antonymy, if the positive form is conjunctive, the negative antonym (its negation) is disjunctive.

                                          theorem Semantics.Lexical.Adjective.deMorgan_disjunctive_conjunctive {α : Type} (dims : List (αBool)) (x : α) :
                                          (!disjunctiveBinding dims x) = conjunctiveBinding (List.map (fun (d : αBool) (a : α) => !d a) dims) x
                                          structure Semantics.Lexical.Adjective.GradableMLScale (α : Type u_1) [LinearOrder α] (W : Type u_2) extends Core.Scale.DirectedMeasure α W :
                                          Type (max u_1 u_2)
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                                            def Semantics.Lexical.Adjective.marginalityPositive {α : Type u_1} [LinearOrder α] (ml : MLScale α) (norm degree : α) :
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                                              theorem Semantics.Lexical.Adjective.marginality_entails_standard {α : Type u_1} [LinearOrder α] (ml : MLScale α) (norm degree : α) (h : marginalityPositive ml norm degree) :
                                              norm < degree

                                              Connecting concrete Degree max to abstract DirectedMeasure #

                                              Degree max has LinearOrder and BoundedOrder (from Core.MeasurementScale), so the abstract theorems in MeasurementScale.lean apply directly to concrete RSA degree computations.

                                              theorem Semantics.Lexical.Adjective.degree_admits_optimum {max : } (h : 1 max) :
                                              ∃ (P : Core.Scale.Degree maxProp), (∀ (x y : Core.Scale.Degree max), x yP xP y) ¬∀ (x y : Core.Scale.Degree max), P x P y