Knowledge Base Inference for Regular Expression Queries
Table 6: KBC Performance on FB15k and Wiki100
['[EMPTY]', '[BOLD] MRR', '[BOLD] HITS@1', '[BOLD] HITS@10']
Given a scoring function ϕ, for (e1,r,e2) ∈T, the log-likelihood loss minimizes: −2∗ϕ(e1,r,e2)+log(∑e′2∈Eϕ(e1,r,e′2))+log(∑e′1∈Eϕ(e′1,r,e2)) (16) For FB15k, we got a marginal improvement of 0.83% points in Hits@10 and 1.1% points in MRR compared to Trouillon et al. We attribute this to using full softmax, instead of a fixed number of negative samples. For Wiki100, we establish the baseline of 46.27% Hits@10 and 31.51% MRR.