This is done via translations, LLM are good at translations, being able to translate doesn't mean you understand the subject.
And no I am not wrong here, I've tested this before, for example if you ask if a CPU model is faster than a GPU model it will say the GPU model is faster, even if the CPU is much more modern and faster overall since it learned that GPU names are faster than CPU names it didn't really understood what faster meant there. Exactly what the LLM gets wrong depends on the LLM of course, and the larger it is the more fine grained these things are but in general it doesn't really have much that can be called understanding.
If you don't understand how to break the LLM like this then you don't really understand what the LLM is capable of, so it is something everyone who uses LLM should know.