WSABIE uses WARP loss and gradient-based updates to minimize the distance between the latent representations of the predicate target and the correct frame, while maximizing the distance to all the other irrelevant frames.
if the predicate is unknown to the lexicon, p / ∈ L, the overall bestscoring frame is chosen.