2) takes as input a single chain of documents {ĥ 1 , • • • ,ĥ T } from one of the chains in the 'reasoning tree' created by the DE, and tries to predict a candidate answer from the last documentĥ T in that reasoning chain.
we adopt an LSTM-RNN with an attention mechanism (Bahdanau et al., 2015) to encode theĥ T to ancestor-aware representations y by attending to [ĥ 1,...,T −1 ].