In particular, for document d 1 , we should rank higher the sentences that are more relevant than the snippet of d 2 : In our implementation, d ′ is a subset of d 1 composed by the sentences that contain at least one non-stop query term.
as such, we have a preference dataset about d 1 : the gradient training set for the sentence scoring function can be defined as: where x 1 and x 2 are feature vectors for s 1 and s 2 respectively.