The drawback of LSTMs or BLSTMs is that we represent a very long sentence as a single vector which is the output of the last time step.
using BLSTM with Neural Attention (NA) mechanism, we represent the sequence of vectors as a combined weighted representation vector by selectively attending to the past outputs.