Comment by rramadass

Very Neat! Appreciate your sharing this.

Just to be clear, your "EXAMPLE OUTPUT" is what is then fed to your prolog meta-interpreter to generate executable code in some other language (you mentioned Groovy) which is actually run i.e. answers the user query. Essentially then, a context is bounded by "pidgin Prolog" (i.e. Prolog+Natural Language) for the LLM and then user queries in Natural Language are submitted against it to generate valid Prolog code. This can be thought of as the logic/constraints of Prolog inference engine in the input modulating the interpretation/inference of the accompanying natural language by the LLM to keep it "on the straight and narrow" towards an accurate output.

I was actually thinking of using "Structured English" (https://en.wikipedia.org/wiki/Structured_English) for this and maybe build a CASE Tool using LLMs for round-trip software engineering.