What is the current state of "correspondence between fed text and output text"? I.e. how much, when fed in the training e.g. that "Spain invested 6000$ in Colum

What is the current state of "correspondence between fed text and output text"? I.e. how much, when fed in the training e.g. that "Spain invested 6000$ in Columbus' first voyage", LLMs will repeat that notion exactly? This, without taking into account reasoning and consistence. And already this notion that I picked randomly is not without issues: dollars how computed? And, it is not difficult to state that Columbus reached the Caribbeans in 1492; more complex to "decide" the year of the siege of Troy out of the many dates proposed. But already at the simplified level of determined clear notions: if LLMs are told that "A is B", and in absence of inconsistency in the training corpus, what is the failure rate (i.e. then outputting something critically different)? > ways to check up Some LLMs work as search engines, outputting not just their tentative answer but linked references. A reasonably safe practice at this stage is to use LLMs that way: ask then use the output to check the reference.