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Linglib.Theories.Processing.Lexical.Discriminative.Measures

DLM-derived semantic-support measures #

@cite{baayen-2019} @cite{gahl-baayen-2024} @cite{saito-tomaschek-baayen-2025} @cite{heitmeier-chuang-baayen-2026}

Sibling to Defs.lean and Normed.lean. Hosts the family of semantic support measures derived from a trained LinearDiscriminativeLexicon — the per-coordinate, per-word, and per-region projections of production that consumer studies have come to rely on.

What is in this file #

Carriers #

Specialised to FormVec n / MeaningVec d (i.e. Fin n → ℝ / Fin d → ℝ), the most common DLM carrier types. All current consumers (ChuangEtAl2026, LuChuangBaayen2026, Saito2025, GahlBaayen2024) use these. A Measures/EuclideanSpace.lean sibling can host inner-product-typed variants if a future consumer needs cosine similarities directly.

Graduation history #

These measures lived inline in Phenomena/Phonology/Studies/Saito2025.lean as the only consumer at first landing (CHANGELOG 0.231.17). Per CLAUDE.md's ≥-2-consumers graduation rule, they lifted to substrate when @cite{gahl-baayen-2024} landed as the second paper-anchored consumer (CHANGELOG 0.231.18). The cross-paper concept of "semantic support for form" is general DLM theory, not paper-specific.

Semantic support for coordinate j of the form vector predicted from meaning vector s: semSup D s j = D.production s j.

The substrate's D.production s j already provides this directly; the named binding makes the cross-paper concept (paper §3.1 eq. 1 of @cite{saito-tomaschek-baayen-2025}; the per-triphone support of @cite{gahl-baayen-2024} §3.4) grep-able.

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    Word-level semantic support — the sum of semSup over a word's component form coordinates. In the consumer studies' triphone- based form representation, this is the sum over the word's component triphones (paper §3.4 of @cite{gahl-baayen-2024} terms this Semantic Support for Form; paper §3.1 eq. 2 of @cite{saito-tomaschek-baayen-2025} terms it SemSupWord).

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      semSup is linear in the meaning vector #

      Since D.production is a LinearMap, semSup D · j is a linear functional on the meaning space. Three structural lemmas (additivity, scalar-multiplication, zero) follow by map_add / map_smul / map_zero on the production map. @[simp] so consumers can rewrite linear-combination meaning vectors directly.

      @[simp]
      theorem Theories.Processing.Lexical.Discriminative.semSup_add {n d : } (D : LinearDiscriminativeLexicon (FormVec n) (MeaningVec d)) (s₁ s₂ : MeaningVec d) (j : Fin n) :
      semSup D (s₁ + s₂) j = semSup D s₁ j + semSup D s₂ j
      @[simp]
      theorem Theories.Processing.Lexical.Discriminative.semSup_smul {n d : } (D : LinearDiscriminativeLexicon (FormVec n) (MeaningVec d)) (c : ) (s : MeaningVec d) (j : Fin n) :
      semSup D (c s) j = c * semSup D s j

      semSupWord zero case #

      semSupWord D 0 js = 0 follows from semSup_zero plus List.sum of the constant-zero list. The general semSupWord_add / semSupWord_smul linearity (sum of linear functionals is linear) is deferred until a consumer needs to rewrite linear-combination meaning vectors at the word level — induction on js plus ring at the cons step works once Mathlib.Tactic.Ring is imported, but no current consumer requires it.

      @[simp]