Documentation

Linglib.Phenomena.Questions.Studies.Dayal2025

Bridge: Left Periphery Theory -> Embedding/Typology Data #

@cite{dayal-2025} @cite{mccloskey-2006}

Connects the left-peripheral selection class theory from Theories.Semantics.Questions.LeftPeriphery to the empirical embedding data in Phenomena.Questions.Embedding and cross-linguistic typology data in Phenomena.Questions.Typology.

Sections F and G from the original LeftPeriphery module: per-datum verification against embedding judgments, shiftiness predictions, and cross-linguistic Q-particle predictions.

source
def Phenomena.Questions.LeftPeripheryBridge.classifyVerb :
String → Semantics.Questions.LeftPeriphery.SelectionClass

Classify each empirical datum from Phenomena.Questions.Embedding.

Equations
Instances For
    source
    theorem Phenomena.Questions.LeftPeripheryBridge.theory_predicts_embedding (d : Embedding.EmbeddingDatum) :
    d ∈ Embedding.allEmbeddingData → Semantics.Questions.LeftPeriphery.allowsEmbedding (classifyVerb d.verb) Semantics.Questions.LeftPeriphery.EmbedType.subordination false false = d.subordination ∧ Semantics.Questions.LeftPeriphery.allowsEmbedding (classifyVerb d.verb) Semantics.Questions.LeftPeriphery.EmbedType.quasiSubordination false false = d.quasiSubordination ∧ Semantics.Questions.LeftPeriphery.allowsEmbedding (classifyVerb d.verb) Semantics.Questions.LeftPeriphery.EmbedType.quotation false false = d.quotation

    The theory correctly predicts all embedding judgments from the data.

    source
    theorem Phenomena.Questions.LeftPeripheryBridge.shiftiness_predicted :
    Semantics.Questions.LeftPeriphery.allowsQuasiSub Semantics.Questions.LeftPeriphery.SelectionClass.responsive Embedding.remember_bare.negated Embedding.remember_bare.questioned = Embedding.remember_bare.quasiSubOk ∧ Semantics.Questions.LeftPeriphery.allowsQuasiSub Semantics.Questions.LeftPeriphery.SelectionClass.responsive Embedding.remember_negated.negated Embedding.remember_negated.questioned = Embedding.remember_negated.quasiSubOk ∧ Semantics.Questions.LeftPeriphery.allowsQuasiSub Semantics.Questions.LeftPeriphery.SelectionClass.responsive Embedding.remember_questioned.negated Embedding.remember_questioned.questioned = Embedding.remember_questioned.quasiSubOk

    Shiftiness predictions match McCloskey's data for remember (responsive).

    source
    def Phenomena.Questions.LeftPeripheryBridge.classifyCrossLingVerb :
    String → Semantics.Questions.LeftPeriphery.SelectionClass

    Classify Hindi-Urdu verbs from the cross-linguistic shiftiness data.

    Equations
    Instances For
      source
      theorem Phenomena.Questions.LeftPeripheryBridge.cross_linguistic_shiftiness_predicted (d : Typology.CrossLingShiftinessDatum) :
      d ∈ Typology.allCrossLingShiftinessData → Semantics.Questions.LeftPeriphery.allowsQuasiSub (classifyCrossLingVerb d.verb) d.negated d.questioned = d.quasiSubOk

      Hindi-Urdu shiftiness follows the same derivation as English: responsive predicates reject quasi-sub in bare form, allow under negation/questioning. The theory predicts ALL cross-linguistic data.

      source
      theorem Phenomena.Questions.LeftPeripheryBridge.particle_layer_predicts_embedding (d : TypologyBridge.QParticleDatum) :
      d ∈ TypologyBridge.allQParticleData → (d.layer = Semantics.Questions.QParticleLayer.cp → d.inSubordinated = true) ∧ (d.layer = Semantics.Questions.QParticleLayer.perspP → d.inSubordinated = false) ∧ (d.layer = Semantics.Questions.QParticleLayer.sap → d.inQuasiSub = false)

      Q-particle embedding follows from which left-peripheral layer they occupy. CP-layer particles appear in subordination; PerspP and SAP particles do not.

      source
      theorem Phenomena.Questions.LeftPeripheryBridge.derived_class_matches_manual :
      Semantics.Questions.LeftPeriphery.deriveSelectionClass Fragments.English.Predicates.Verbal.know = classifyVerb "know" ∧ Semantics.Questions.LeftPeriphery.deriveSelectionClass Fragments.English.Predicates.Verbal.wonder = classifyVerb "wonder" ∧ Semantics.Questions.LeftPeriphery.deriveSelectionClass Fragments.English.Predicates.Verbal.ask = classifyVerb "ask" ∧ Semantics.Questions.LeftPeriphery.deriveSelectionClass Fragments.English.Predicates.Verbal.investigate = classifyVerb "investigate" ∧ Semantics.Questions.LeftPeriphery.deriveSelectionClass Fragments.English.Predicates.Verbal.believe = classifyVerb "believe"

      The structurally derived classification matches the manually-assigned string-based classification for all verbs in the embedding data.

      source
      theorem Phenomena.Questions.LeftPeripheryBridge.classifyVerb_agrees_with_selectionClass :
      classifyVerb "know" = Semantics.Questions.LeftPeriphery.fieldSelectionClass Fragments.English.Predicates.Verbal.know ∧ classifyVerb "wonder" = Semantics.Questions.LeftPeriphery.fieldSelectionClass Fragments.English.Predicates.Verbal.wonder ∧ classifyVerb "ask" = Semantics.Questions.LeftPeriphery.fieldSelectionClass Fragments.English.Predicates.Verbal.ask ∧ classifyVerb "investigate" = Semantics.Questions.LeftPeriphery.fieldSelectionClass Fragments.English.Predicates.Verbal.investigate ∧ classifyVerb "depend on" = Semantics.Questions.LeftPeriphery.fieldSelectionClass Fragments.English.Predicates.Verbal.depend_on ∧ classifyVerb "believe" = Semantics.Questions.LeftPeriphery.fieldSelectionClass Fragments.English.Predicates.Verbal.believe

      String-based classification matches field-based derivation.