The Pitfalls of Defining Hallucination
Kees van Deemter
Despite impressive advances in Natural Language Generation (NLG) and Large
Language Models (LLMs), researchers are still unclear about important aspects
of NLG evaluation. To substantiate this claim, I examine current
classifications of hallucination and omission in Data-text NLG, and I propose a
logic-based synthesis of these classfications. I conclude by highlighting some
remaining limitations of all current thinking about hallucination and by
discussing implications for LLMs.