This paper presents a neuro-symbolic hybrid pipeline for SemEval-2026 Task 11 that addresses the content effect in syllogistic reasoning. The system converts natural-language syllogisms into formal mood-figure representations via regex parsing and LLM-powered extraction, then determines validity through symbolic table lookup against the 24 classically valid forms. The approach achieved a perfect Combined Score of 100.0 on Subtask 1 and competitive results on all four subtasks.