Our method works as follows: Paragraph encoding We first represent all tokens p i in a paragraph p as a sequence of feature vectorsp i ∈ R d and pass them as the input to a recurrent neural network and thus obtain: where p i is expected to encode useful context information around token p i .
we choose to use a multi-layer bidirectional long short-term memory network (LSTM), and take p i as the concatenation of each layer's hidden units in the end.