It is worthy to note that, α i t is used as the probability that position index i is selected as output at time step t. At time step t, the position index with the highest probability in α t is greedily sampled as the output O t .
once the attention weights are computed, the context vector c t is computed by: Then c t together with d t−1 are fed into LSTM decoder at time step t: the LSTM decoder is capable of tracking the state of the variable-length entity pair predictor.