As Large Language Models (LLMs) have advanced, they have brought forth new
challenges, with one of the prominent issues being LLM hallucination. While
various mitigation techniques are emerging to address hallucination, it is
equally crucial to delve into its underlying causes. Consequently, in this
preliminary exploratory investigation, we examine how linguistic factors in
prompts, specifically readability, formality, and concreteness, influence the
occurrence of hallucinations. Our experimental results suggest that prompts
characterized by greater formality and concreteness tend to result in reduced
hallucination. However, the outcomes pertaining to readability are somewhat
inconclusive, showing a mixed pattern