This thesis presents OntoNat, a prototypical system for answering Yes/No-questions on natural language sentences. Different from existing systems, OntoNat uses background knowledge from the Suggested Upper Model Ontology (SUMO), so that it can perform some kind of common sense reasoning to answer a question. SUMO is translated to a disjunctive logic program (DLP). The input sentence and the Yes/No-question are also translated to DLPs, in cooperation with the Computational Linguistics Department of Saarland University. These DLPs are given to a first-order theorem-prover (KRHyper), which tries to answer the question.