Question answering and reading comprehension has received a large amount of interest in recent years fuelled by new and large datasets such as CNN News, SQuAD, and MSMARCO. All of these datasets, however, simplify the task in that the provided passage is known to contain the answer. Welbl et al. from UCL introduce QAngaroo, a collection of two new datasets that model the more realistic setting of first having to find the relevant passage. These datasets should drive the development of QA systems and should make them more useful for more realistic applications.