We reimplement BiDAF with simplified parameterizations and change the prediction layer so that it can predict multiple answer spans.
we encode the input story {x 1 , ..., x T } and a given question {q 1 , ..., q J } at the character level and the word level, where the character level uses CNNs and the word level uses pre-trained word vectors.