More specifically, given the input sentence S (containing an answer span) and the preceding context C, we first run a coreference resolution system to get the coref-clusters for S and C and use them to create a coreference transformed input sentence: for each pronoun, we append its most representative non-pronominal coreferent mention.
we apply the simple feedforward network based mention-ranking model of Clark and Manning (2016) to the concatenation of C and S to get the coref-clusters for all entities in C and S. The C&M model produces a score/representation s for each mention pair where W m is a 1 × d weight matrix and b is the bias.