The role of interrogative sentences in political argumentation remains largely unexplored. This study addresses this gap by introducing a new Polish-language dataset featuring diverse examples of interrogative sentences in political discourse (election debates). The dataset serves as a unique resource for theoretical research in Argumentation Mining and Natural Language Inference through the annotation of ⟨IS, C⟩ and ⟨IS, P⟩ pairs, where IS denotes an interrogative sentence, C represents its corresponding conclusion, and P indicates a premise. The annotations primarily capture implicitly expressed argumentative structures and can serve as a benchmark for large language models (LLMs), particularly those trained on Polish-language data. Furthermore, this is the first study in Argumentation Mining where annotators independently verbalize the content of conclusions and premises conveyed through speech acts constructed with interrogative sentences. Our findings reveal that interrogative sentences in political debates most frequently function as implicature (approx. 45%), normative propositions (approx. 31%), statements expressing epistemic states (approx. 20%), and presuppositions (approx. 4%). Semantic similarity analysis confirms that annotators achieve a high level of consistency in identifying and verbalizing the content implied by interrogative sentences. The dataset provides a robust foundation for developing advanced language models and for further research into the role of interrogative sentences in political discourse.