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We present the system we built for participating in SemEval-2016 Task 3 onCommunity Question Answering. We achieved the best results on subtask C, andstrong results on subtasks A and B, by combining a rich set of various types offeatures: semantic, lexical, metadata, and user-related. The most importantgroup turned out to be the metadata for the question and for the comment,semantic vectors trained on QatarLiving data and similarities between thequestion and the comment for subtasks A and C, and between the original and therelated question for Subtask B.

SUper Team at SemEval-2016 Task 3: Building a feature-rich system for community question answering