Semantic Theory
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A Semantic Theory is a theoretical framework that can systematically describe meaning (in language, symbols, or formal systems to enable interpretation, communication, and understanding).
- AKA: Theory of Meaning, Meaning Theory, Semantic Framework, Interpretive System.
- Context:
- It can typically explain Semantic Content through formal representations and systematic rules that capture propositional content and referential connections.
- It can typically model Meaning Relation between linguistic expressions and world entities or mental states through correspondence rules or cognitive mappings.
- It can typically account for Semantic Property such as truth, reference, entailment, and ambiguity through logical structure and interpretive principles.
- It can typically provide Compositional Analysis of how complex expression meanings depend on component meanings and their structural arrangement.
- It can typically formalize Inference Pattern that preserve truth or semantic properties across reasoning steps.
- It can typically distinguish between Semantic Representation and Conceptual Representation in modeling language understanding.
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- It can often address Context Dependence through parameters for speaker, time, location, and other contextual factors that influence interpretation.
- It can often distinguish between Literal Meaning and Pragmatic Meaning based on context and communicative intention in discourse situations.
- It can often model Semantic Change through diachronic analysis and meaning evolution mechanisms across historical periods.
- It can often capture Cross-Linguistic Difference in meaning structure and semantic category through typological comparison and conceptual universals.
- It can often connect Meaning with cognitive processes or social practices through embodied cognition and cultural context.
- It can often distinguish between Speaker Meaning and Conventional Meaning in explaining communication dynamics.
- It can often formalize Vagueness and Gradience in natural language meaning through fuzzy logic or probability distributions.
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- It can range from being a Formal Semantic Theory to being a Cognitive Semantic Theory, depending on its theoretical foundation and explanatory goals.
- It can range from being a Denotational Semantic Theory to being a Conceptual Semantic Theory, depending on its meaning representation and interpretive mechanisms.
- It can range from being a Truth-Conditional Semantic Theory to being a Use-Based Semantic Theory, depending on its meaning criterion and verification method.
- It can range from being a Sentence-Level Semantic Theory to being a Discourse-Level Semantic Theory, depending on its analytical scope and cohesion modeling.
- It can range from being a Static Semantic Theory to being a Dynamic Semantic Theory, depending on its treatment of context and meaning update.
- It can range from being a Monolithic Semantic Theory to being a Modular Semantic Theory, depending on its architectural design and component integration.
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- It can serve Theoretical Objectives including meaning explanation, language understanding, semantic competence modeling, and interpretive system design.
- It can employ Analytical Tools such as logical form, model theory, conceptual structure, frame semantics, and truth-conditional semantics.
- It can integrate with Related Disciplines including syntax, pragmatics, cognitive science, philosophy of language, and artificial intelligence.
- It can address Semantic Phenomenon including reference resolution, quantifier scope, presupposition projection, metonymy, and metaphor interpretation.
- It can identify Meaning Construction Processes including semantic composition, pragmatic enrichment, coercion, and accommodation.
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- Examples:
- Semantic Theory Approach Categories, such as:
- Formal Semantic Theorys, such as:
- Montague Semantics for intensional logic analysis and systematic composition.
- Possible World Semantics for modal expression interpretation and counterfactual reasoning.
- Situation Semantics for partial information modeling and context representation.
- Discourse Representation Theory for anaphora resolution and temporal reference.
- Type-Theoretic Semantics for semantic type system and functional composition.
- Two-Dimensional Semantics for epistemic modality and necessary a posteriori truth.
- Cognitive Semantic Theorys, such as:
- Prototype Theory for category structure explanation and gradience modeling.
- Conceptual Metaphor Theory for metaphorical meaning analysis and embodied abstraction.
- Frame Semantics for encyclopedic knowledge integration and meaning contextualization.
- Mental Space Theory for conceptual integration modeling and blended meaning.
- Conceptual Semantics for lexical decomposition and thematic role assignment.
- Embodied Construction Grammar for sensorimotor grounding and schematic integration.
- Computational Semantic Theorys, such as:
- Distributional Semantics for word meaning vector representation and similarity computation.
- Compositional Distributional Semantics for phrase meaning computation and vector composition.
- Lexical Semantics for word sense representation and polysemy modeling.
- Ontology-Based Semantics for knowledge representation and conceptual hierarchy.
- Neural Semantic Theory for representation learning and semantic embedding.
- Probabilistic Semantics for uncertainty representation and bayesian interpretation.
- Formal Semantic Theorys, such as:
- Semantic Theory Domain Categories, such as:
- Natural Language Semantic Theorys, such as:
- Truth-Conditional Semantics for sentence meaning analysis and proposition verification.
- Dynamic Semantics for context change potential modeling and information update.
- Game-Theoretical Semantics for meaning verification procedure and strategic interaction.
- Inquisitive Semantics for question meaning representation and informational content.
- Experimental Semantics for empirical meaning testing and judgement elicitation.
- Lexical Resource Theory for lexical database construction and sense enumeration.
- Formal System Semantic Theorys, such as:
- Programming Language Semantics for code meaning specification and execution prediction.
- Modal Logic Semantics for possibility expression interpretation and accessibility relation.
- Probabilistic Semantics for uncertainty representation and belief modeling.
- Category Theory Semantics for algebraic structure mapping and morphism interpretation.
- Process Semantics for concurrent system modeling and state transition.
- Game Semantics for interactive computation interpretation and strategic behavior.
- Applied Semantic Theorys, such as:
- Educational Semantic Theory for knowledge representation and conceptual learning.
- Clinical Semantic Theory for patient communication analysis and diagnostic reasoning.
- Legal Semantic Theory for statutory interpretation and precedent formalization.
- Media Semantic Theory for messaging analysis and framing effect.
- Natural Language Semantic Theorys, such as:
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- Semantic Theory Approach Categories, such as:
- Counter-Examples:
- Syntactic Theorys, which focus on grammatical structure rather than meaning and interpretation.
- Pragmatic Theorys, which address language use rather than literal meaning and semantic content.
- Phonological Theorys, which study sound patterns rather than semantic content or meaning relations.
- Etymological Analysis, which traces word history rather than systematic meaning or interpretive principles.
- Statistical Language Models, which capture distributional patterns without semantic interpretation or meaning explanation.
- Rhetorical Theorys, which analyze persuasive effect rather than truth conditions or referential content.
- Narrative Theorys, which examine story structure rather than propositional content or semantic composition.
- See: Compositionality, Reference, Truth Condition, Lexical Semantics, Formal Semantics, Meaning, Interpretation, Model Theory, Denotation, Connotation, Semantic Network, Conceptual Structure.