I'm not aware of evidence that support that claim. If I ask ChatGPT "Give me a recipe for squirrel lemon stew" and it so happens that one person did write a recipe for that exact thing on the Internet, then I would expect that the most accurate, truthful response would be that exact recipe. Anything else would essentially be hallucination.
You can certainly try to hit a nail with a screw driver, but that doesn't make the screw driver a hammer.
Of course, if I ask a question that isn't as well served by the corpus, it has to do its best to interpolate an answer from what it knows.
But ultimately its job is to extract information from a corpus and serve it up with as much semantic fidelity to the original corpus as possible. If I ask how many moons Earth has, it should say "one". If I ask it what the third line of Poe's "The Raven" is, it should say "While I nodded, nearly napping, suddenly there came a tapping,". Anything else is wrong.
If you ask it a specific enough question where only a tiny corner of its corpus is relevant, I would expect it to end up either reproducing the possibly copyright piece of that corpus or, perhaps worse, cough up some bullshit because it's trying to avoid overfitting.
(I'm ignoring for the moment LLM use cases like image synthesis where you want it to hallucinate to be "creative".)
And you probably wouldn't want to - if I ask if donuts are radioactive and one person explicitly said that on the internet you probably aren't going to tell me you want it to spit out that answer just because it exactly matches what you asked. You want it to learn from the overwhelimg corpus of related knowledge that says donuts are food, people routinely eat them, etc etc and tell you they aren't radioactive.