To illustrate the effectiveness of this idea, we parameterize p κ (w|q) with a general-purpose neural labeling model, which consists of a word embedding layer, two layers of BiGRU, and a linearchain conditional random field (CRF).
given a question q of length T , the score of a sequence label configuration y ∈ R T is where H(q) is the hidden output of the top-layer BiGRU, A is the transition matrix possesed by the CRF, and [•] i,j indicates the matrix element on row i collum j.