We use LSTMs with hidden states of size 150 for the answer module vs. those of size 100 for the question module since the answer module is less memory intensive than the question module.
to train the answer synthesis module, we further augment the human-annotated labels of each paragraph with tags from a simple NER system 6 because labels of answers provided in the train set are underspecified, i.e., many words in the paragraph that could be potential answers are not labeled.