To solve the FDKB task using KBR, one feasible way is to exhaustively calculate the scores of all (r, t) combinations for the given head entity h. Afterwards, the highly-scored facts are returned as results.
semantic matching models such as REsCAL (Nickel et al., 2011), DistMult (Yang et al., 2014), Complex (Trouillon et al., 2016), HolE (Nickel et al., 2016) and ANALOGY (Liu et al., 2017) model the score of triples by the semantic similarity.