37.2326, Diss: Indo-European; English; Cognitive Science, Philosophy of Language, Pragmatics, Psycholinguistics, Semantics: Zhengjie Situ: "Copredication as Dynamic Frame Composition in Discourse"

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LINGUIST List: Vol-37-2326. Mon Jul 13 2026. ISSN: 1069 - 4875.

Subject: 37.2326, Diss: Indo-European; English; Cognitive Science, Philosophy of Language, Pragmatics, Psycholinguistics, Semantics: Zhengjie Situ: "Copredication as Dynamic Frame Composition in Discourse"

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Date: 10-Jul-2026
From: Zhengjie Situ [stuzenjay at gmail.com]
Subject: Copredication as Dynamic Frame Composition in Discourse


Institution: University of Edinburgh
Program: School of Philosophy, Psychology, and Language Sciences
Degree Date: 2026
Level: PhD

Author: Zhengjie Situ

Dissertation Title: Copredication as Dynamic Frame Composition in
Discourse

Dissertation URL: https://doi.org/10.7488/era/7083

Linguistic Field(s): Cognitive Science
                     Philosophy of Language
                     Pragmatics
                     Psycholinguistics
                     Semantics

Subject Language(s): English (eng, stan1293)

Language Family(ies): Indo-European (indo1319)

Dissertation Director(s): Chris Cummins, Hannah Rohde, Wataru Uegaki

Dissertation Abstract:

This dissertation develops a unified, cognitively plausible account of
copredication: the pervasive linguistic phenomenon where a single
nominal expression simultaneously satisfies multiple predicates
requiring distinct and often incompatible facets (e.g., That book is
heavy but informative; Lunch was delicious but lasted hours). While
ubiquitous in everyday language, copredication poses a fundamental
challenge to theories of meaning composition by demanding simultaneous
access to different aspects of a single entity. This work argues that
such phenomena expose the critical limitations of static, type-driven
accounts of the lexicon.
The dissertation critically evaluates the dominant approach, static
lexicalism, exemplified by the Generative Lexicon (GL). It
demonstrates that GL's reliance on precompiled complex entries
("dot-types") systematically fails to capture the dynamic signature of
copredication. Specifically, GL cannot adequately explain pervasive
predicate-order asymmetries, where reversing predicates alters
acceptability; the graded and context-sensitive nature of felicity;
the persistent accessibility of unselected facets for anaphora (the
"destructive projection" problem); or the complex "doubledistinctness"
constraints required for quantification.
To address these limitations, this work introduces the Entity
Enrichment (EE) model, which shifts the explanatory load from the
lexicon to the mechanisms of discourse processing. Adopting a "thin
lexicon, rich construction" architecture, EE posits that
interpretation is a sequential process where hearers incrementally
build a unitary discourse referent. The model recasts selectional
restrictions not as static types, but as dynamic, defeasible
presuppositions.
The EE framework is formalized within a two-tier architecture that
maintains a strict separation between dynamic discourse files and
stable, frame-based conceptual knowledge. The enrichment engine
utilizes three core constructive operators: Aspect Introduction, Macro
Introduction, and Cascade Introduction. These operators are governed
by a single Cost-Coherence Calculus, which adjudicates the trade-off
between interpretive coherence and processing effort.
This procedural, cost-sensitive architecture yields a falsifiable
prediction: the Central-toPeripheral Processing Advantage. This
principle posits that integrating conceptually central facets incurs
lower processing costs than integrating peripheral ones, predicting
measurable asymmetries in predicate ordering. This prediction is
substantiated by an experimental study using an acceptability
judgement task. The analysis, employing a cumulative link
mixed-effects model (CLMM), reveals a significant penalty for
Peripheral-first orderings (Odds Ratio ≈ 0.20), providing evidence
that the interpretation of copredication is incremental and
asymmetrical.
The dissertation further demonstrates the framework’s analytical
breadth (Chapter 8) through derivations and case studies, extending
the analysis to verbal facet-mixing, kind-instance copredication,
fictional cross-world predication, and the resolution of
quantificational ambiguity via the Joint-Salience Individuation (JSI)
presupposition. It also proposes a cost-based division of labor
between low-cost Entity Enrichment and high-cost Predicate Transfer
(PT), a metalinguistic repair mechanism. By replacing static
type-selection with a dynamic enrichment mechanism, the EE framework
attempts to give a unified account that integrates formal analyses
with cognitive plausibility, illuminating how multifaceted meanings
are constructed in real time.



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