  Several large cloze-style context-question-answer datasets have been
introduced recently: the CNN and Daily Mail news data and the Children's Book
Test. Thanks to the size of these datasets, the associated text comprehension
task is well suited for deep-learning techniques that currently seem to
outperform all alternative approaches. We present a new, simple model that uses
attention to directly pick the answer from the context as opposed to computing
the answer using a blended representation of words in the document as is usual
in similar models. This makes the model particularly suitable for
question-answering problems where the answer is a single word from the
document. Ensemble of our models sets new state of the art on all evaluated
datasets.
