You'll have to be more specific than that. For me what I point out is obvious: Prolog is not magick. Your program won't magickally reason if you write it in Prolog, much less reason correctly. If an LLM translates a Problem to the wrong Prolog program, Prolog won't magickally turn it into a correct program. And that's just rephrasing what I said in my comment above. There's really not much more to say.
Here's just one more observation: the problems where translating reasoning to Prolog will work best are problems where there are a lot of examples of Prolog to be found on the web, e.g. wolf-cabbage-goat problems and the like. With problems like that it is much easier for an LLM to generate a correct translation of the problem to Prolog and get a correct solution just because there's lots of examples. But if you choose a problem that's rarely attacked with Prolog code, like, I don't know, some mathematical problem that obtains in nuclear physics as a for instance, then an LLM will be much more likely to generate garbage Prolog, while e.g. Fortran would be a better target language. From what I can see, the papers linked in the article above concentrate on the Prolog-friendly kind of problem, like logical puzzles and the like. That smells like cherry picking to me, or just good, old confirmation bias.
Again, Prolog is not magick. The article above and the papers it links to seem to take this attitude of "just add Prolog" and that will make LLMs suddenly magickally reason with fairy dust on top. Ain't gonna happen.