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Syntactic Consequence (⊢) Versus Semantic Consequence (⊨)

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Logical Consequence and EntailmentSoundness and Completeness of First-Order Logic+1 moreGödel's Completeness Theorem for First-Order LogicLogical Consequence and Validity
consequence entailment soundness completeness

Core Idea

Γ ⊢ φ (syntactic consequence) means φ can be derived from Γ using inference rules of a proof system. Γ ⊨ φ (semantic consequence) means φ is true in all models where Γ is true. The two notions are distinct: ⊢ is about provability, ⊨ is about validity. Soundness says ⊢ ⇒ ⊨ (no false proofs), and completeness says ⊨ ⇒ ⊢ (no missing proofs). For first-order logic, completeness holds, so the two notions coincide. Understanding their relationship is key to foundational logic.

How It's Best Learned

Illustrate with examples in propositional logic using truth tables. Discuss a simple proof system and verify soundness. Distinguish the two notions by considering unprovable but valid formulas (before completeness is proved) and unprovable invalid formulas. Understand that completeness is a non-trivial metatheorem, not an axiom.

Common Misconceptions

Explainer

You already know that logical consequence (⊨) is a semantic relation — Γ ⊨ φ when φ is true in every model satisfying Γ — and you know the soundness and completeness results for both propositional logic and first-order logic. The distinction between and is the distinction between *how reasoning is implemented* and *what reasoning is about*. One is a mechanical, syntactic procedure; the other is a mathematical relationship defined by truth in models. They answer the same question from different angles.

Concretely: Γ ⊢ φ says that starting from Γ, you can derive φ by applying the rules of some proof system in a finite sequence of steps. The derivation is a formal object — a string of symbols manipulated according to fixed rules, with no reference to meaning. Γ ⊨ φ says that for every interpretation that makes Γ true, that interpretation also makes φ true. This is an infinitary claim about all possible models, which may be uncountable in number. The two notions are defined entirely independently; their relationship is a theorem, not a definition.

Soundness (⊢ implies ⊨) is proved by structural induction on proofs: every axiom is semantically valid, and every rule of inference preserves truth. This shows the proof system is trustworthy — it cannot derive something false from true premises. Completeness (⊨ implies ⊢) is the non-trivial direction. For propositional logic, completeness can be established by a truth-table argument or by a normal form argument. For first-order logic, Gödel's 1929 proof constructs a model from "syntactic objects" — maximal consistent sets of sentences — and shows that the constructed model satisfies exactly what is consistent with Γ. Completeness says the proof system is *powerful enough* to capture all semantic truth.

With both soundness and completeness in hand, ⊢ and ⊨ are extensionally equivalent for first-order logic: Γ ⊢ φ if and only if Γ ⊨ φ. This does *not* mean they are the same concept. They can diverge in weaker or stronger logics: second-order logic is sound but *not complete* — there are semantic truths with no second-order proof. Intuitionistic logic has a proof system that differs from classical logic even though both target "truth in models." The distinction between ⊢ and ⊨ remains conceptually crucial even when they coincide, because it separates the question of *what can be proved* (a computational, proof-search question) from *what is true* (a model-theoretic question). Completeness is the lucky coincidence that, for classical first-order logic, the two questions have the same answer.

Practice Questions 5 questions

Prerequisite Chain

Understanding ZeroThe Number ZeroCounting to FiveCounting to 10Counting to 20Counting a Set of Objects Up to 20Cardinality: The Last Number CountedMatching Numerals to QuantitiesSubitizing Small QuantitiesAddition Within 10Number Bonds to 10Addition Within 20Doubles and Near DoublesDoubles Facts Within 10Near Doubles Facts Within 20Mental Math Strategies for AdditionMental Math: Adding and Subtracting TensAddition Within 100Repeated Addition as MultiplicationMultiplication as Equal GroupsMultiplication: ArraysBasic Multiplication Facts (0s, 1s, 2s, 5s, 10s)Multiplication Facts Within 100Division as Equal SharingDivision as Grouping (Measurement Division)Division: Grouping (Repeated Subtraction) ModelDivision: Fair Sharing ModelDivision as Equal SharingDivision as GroupingBasic Division FactsDivision Facts Within 100Multiplication and Division Fact FamiliesRelationship Between Multiplication and DivisionDivision Facts as Inverse of MultiplicationRemainders and Quotients in DivisionDivision Word ProblemsMulti-Step Word ProblemsSolving Multi-Step Word ProblemsMultiplication Word ProblemsDivision Word ProblemsIntroduction to Long DivisionFactors and MultiplesPrime and Composite NumbersEquivalent FractionsRelating Fractions and DecimalsDecimal Place ValueIntegers and the Number LineComparing and Ordering IntegersAbsolute ValueAdding IntegersSubtracting IntegersMultiplying IntegersIntroduction to ExponentsOrder of OperationsInteger Order of OperationsVariable ExpressionsThe Distributive PropertyVariables and Expressions ReviewIntroduction to PolynomialsAdding and Subtracting PolynomialsMultiplying PolynomialsFactorialPermutationsCombinationsCounting Principles: Addition and Multiplication RulesIntroduction to Graph TheoryPropositional Logic FoundationsLogical EquivalencesBoolean AlgebraIntroduction to Propositional LogicIntroduction to Predicate Logic (First-Order Logic)First-Order Logic SyntaxTerms and Atomic Formulas in FOLVariable Binding and ScopeOpen and Closed Formulas in First-Order LogicVariable Substitution and Capture-Avoidance in First-Order LogicQuantifier Instantiation Rules in First-Order Proof SystemsUniversal Quantification: Meaning and ScopeFree Variables and Bound VariablesSubstitution and Instantiation in Predicate LogicTerms and Atomic FormulasFormulas and Well-Formed ExpressionsStructures and InterpretationsModel Interpretation and SatisfactionInterpretation, Truth, and Satisfaction of FormulasLogical Consequence and EntailmentSyntactic Consequence (⊢) Versus Semantic Consequence (⊨)

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