Question Answering (QA) systems provide a user-friendly way to access any type of knowledge base and especially for Linked Data sources to get insight into semantic information. But understanding natural language, transferring it to a formal query and finding the correct answer is a complex task. The challenge is even harder when the QA system aims to be easily adaptable regarding the underlying information. This goal can be achieved by an approach that is independent from the knowledge base. Thereby, the respective data can be replaced or updated without changes on the system itself. With this paper we present our QA approach and the demonstrator which is able to consume natural language questions of general knowledge (not specific to a topic or domain).