Teaching Machines to Read and Comprehend

  title={Teaching Machines to Read and Comprehend},
  author={Karl Moritz Hermann and Tom{\'a}s Kocisk{\'y} and Edward Grefenstette and Lasse Espeholt and Will Kay and Mustafa Suleyman and Phil Blunsom},
Teaching machines to read natural language documents remains an elusive challenge. Machine reading systems can be tested on their ability to answer questions posed on the contents of documents that they have seen, but until now large scale training and test datasets have been missing for this type of evaluation. In this work we define a new methodology that resolves this bottleneck and provides large scale supervised reading comprehension data. This allows us to develop a class of attention… CONTINUE READING
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  • The chart shows the precision for each decile in document lengths across the corpus as well as the precision for the 5% longest articles.



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