A Non-commutative Bilinear Model for Answering Path Queries in Knowledge Graphs
Table 3: Path QA ranking result: Comparing BlockHolE (b=2,m=25 and b=4,m=25) to other bilinear models. The dimension of the embedding space for DistMult, ComplEx and RESCAL was set to n=50 as the result of grid search.
['[EMPTY]', 'WN11 Base', 'WN11 Base', 'WN11 Deduction', 'WN11 Deduction', 'WN11 Induction', 'WN11 Induction', 'FB13 Base', 'FB13 Base', 'FB13 Deduction', 'FB13 Deduction', 'FB13 Induction', 'FB13 Induction']
BlockHolE outperforms other bilinear KGE models considerably both on deductive and inductive test settings. These results strongly suggest that BlockHolE is more expressive in modeling path QA than DistMult and ComplEx, while effectively reducing redundant parameters in RESCAL which can cause model overfitting. =bm of the embedding space.