Then (y, h) corresponds to an eMRG, and (a, c) ∈ (y, h) is a labeled edge a attached with a textual evidence c. Given a labeled dataset D = {(x 1 , y 1 ), ..., (x n , y n )} ∈ (X × Y) n , we aim to learn a discriminant function f : X → Y × H that outputs the optimal eMRG (y, h) ∈ Y(x) × H(x) for a given sentence x.
these methods fall short of extracting comparative relations based on domain dependent information.