Structural Influence and Tonal Nuance in GPT: Five Semantically Safe One-Turn Observations

This report provides observational data from five one-turn GPT prompts that exhibited subtle behavioral nuances, despite being free of semantically sensitive content. These examples offer insight into how syntactic features—such as rhythm and phrasing—may correlate with tonal variation in language model responses.Rather than aiming for manipulation or control, this study contributes to the understanding of how structural input characteristics may inform safer and more predictable LLM design.This publication is the Japanese counterpart to the English-language entry titled Syntactic Resonance-Induced Perturbations in GPT: Five One-Turn Examples within Semantically Safe Zones.