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A fundamental use of knowledge bases (KBs) is query answering, i.e., retrieving the information entailed by the KB in response to a user query. When both the KB and the query are specified as logical formulae, the standard form of answer provided to users is the set of all certain answers (CAs): tuples of constants that satisfy the formula defining the query in every model of the logical theory defining the KB. Despite their wide adoption, CAs are known to be just a lossy representation of the information that a KB and a query provide. While several alternative answer languages have been proposed in the literature, no general consensus has emerged on the most suitable approach to query answering over ontological KBs, as each language comes with its own limitations. To address some of these issues, we introduce Regularly Recurrent Answers (RRAs), a novel answer language for queries over ontological KBs based on regular expressions. RRAs support the representation of infinite sets of tuples of constants via a simple (and arguably well understood) generation mechanism. We show that RRAs can capture a fundamental fragment of the certain information entailed by union of conjunctive queries and DL-Lite KBs, making them a strong candidate for informative query answering settings. Our contribution includes the formal definition of RRAs, a proof of their informativeness, and a study of the computational complexity of query answering problem using RRAs.