This paper describes the AnswerSeeker question answering engine, a modular and extensible framework that allows integrating multiple approaches to question answering in one system. It supports the two major approaches to question answering, knowledge annotation and knowledge mining. In addition, it proposes one novel approach to question interpretation which abstracts from the original formulation of the question. Text patterns are used to interpret a question and to extract answers from text snippets. Our system automatically learns the patterns for answer extraction, using question-answer pairs as training data. Experimental results reveal the potential of AnswerSeeker.