It can be seen that the proposed Di-alKG Walker model outperforms other state-ofthe-art baselines, especially for recalls at small ks.
when textual contexts are added as input (E+S and E+S+D), the model learns to condition its walk path output on textual contexts, thus outperforming the non-textual ablation model (E).