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Machine reading systems can be tested on their ability to answer\nquestions posed on the contents of documents that they have seen, but until now\nlarge scale training and test datasets have been missing for this type of\nevaluation. In this work we define a new methodology that resolves this\nbottleneck and provides large scale supervised reading comprehension data. 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