For first-order logic, every semantically valid consequence has a formal proof. Keeping the exact identity in view prevents the geometric or probabilistic intuition from drifting.
Objects and notation
A first-order language \(\mathcal L\) supplies symbols, formulas, and structures. Semantic consequence \(T\models\varphi\) is truth in every model, while provability \(T\vdash\varphi\) is a finite formal derivation.
There are two layers here: the object \(\mathsf D\) and the law \(\mathsf C\). Writing them separately makes the direction of \(\Longrightarrow\) visible and keeps an accidental converse from slipping in.
Push the symbols
A worked instance is useful here because it exposes every index that the compressed statement hides.
Structural reading
The abstraction earns its keep by explaining why the same computation reappears. The notation compresses repeated reasoning without erasing the hypothesis that licenses it.
A hypothesis worth keeping
First-order compactness does not apply to arbitrary second-order properties. Finiteness and categorical characterization of the natural numbers lie beyond its direct reach.
With the dependency made explicit, the same pattern can be recognised safely in nearby problems. A changed hypothesis should now be easy to spot.