Can I formalize an expert system as a OWL knowledge base, rules, input and classes as a classifikator function like a neural network?

Question

A neural network f is defined as a function that maps instances of input X to labels of Y as follows:

f: X --> Y

Let us assume that an expert system has a knowledge base K modelled as a OWL ontology, rules are expressed in SWRL and the set of rules is represented by R. For classification, X is loaded / imported into K (i.e. the ontology) where every instance of x is represented as an individual in K, thus X ⊆ K.

The classification is done by applying the rules of R on K that contains X. The classification (defining the type) of instances (i.e. individuals of X) to a class of Y is conducted by a rule engine.

Defining my expert system w.r.t. to the definition of a neural network, can I say that: the expert system's rule engine is f that infer based on R to which class y_i of Y ⊆ K the inputs of x_i of X are a type of?

Meaning the expert system also can be formalized as:

f: X --> Y

I think it should be possible since in both cases we have a classificator. But how can I express the difference of the inner working of f, thus, if is a neural network or an expert system?

Thanks for any comments on this