In this paper we use bidirectional LSTMs as a way of representing elements in a sequence (i.e., words or sentences) together with their contexts, capturing the element and an "infinite" window around it.
we run a bidirectional LSTM over sentence T , and take the output as the representations of words in T , where h t ∈ R k is the output vector for word u t based on its context.