An expert system is generically a system of declarative rules, capturing an expert's knowledge, that can be used to solve problems.
Traditionally expert systems are symbolic systems, representing the rules in a language such as Prolog, with these rules having been laboriously hand derived, but none of this seems core to the definition.
A pre-trained LLM can be considered as an expert system that captures the rules of auto-regressive language generation needed to predict the training data. These rules are represented by the weights of a transformer, and were learnt by SGD rather than hand coded, but so what?
Expert systems are a specific kind of thing (see https://en.wikipedia.org/wiki/Expert_system#Software_archite...): any definition you've read is a description. If the definition includes GPT models, the definition is imprecise.
Would you quibble if an expert system was procedurally coded in C++ rather than in Prolog? "You see this pattern, do this".
You could compile an expert system into C++, and I'd still call it an expert system (even if the declarative version was never written down), but most C++ programs are not expert systems. Heck, a lot of Prolog programs aren't! To the extent a C++ program representing GPT inference is an expert system, it's the trivial expert system with one fact.