Glossary
An answer that sounds plausible and is factually wrong. The model does not invent deliberately, it strings likely words together.
Language models predict the next token. Whether the result is true is not a category in that process. That is why wrong answers sound exactly as convincing as right ones.
It happens most where training data is thin: niche products, internal names, recent events, exact figures and citations.