In this paper we describe and evaluate a Question Answering system that goes beyond answering factoid questions. We focus on FAQlike questions and answers, and build our system around a noisy-channel architecture which exploits both a language model for answers and a transformation model for answer/question terms, trained on a corpus of 1 million question/answer pairs collected from the Web.