\spexkge: A Location-Aware Knowledge Graph Embedding Model for Geographic Question Answering and Spatial Semantic Lifting
Table 5: The evaluation of spatial semantic lifting on DBGeo over all validation/testing triples
['[EMPTY]', '\\spexkge  [ITALIC] space AUC', '\\spexkge  [ITALIC] space APR', '\\spexkge  [ITALIC] ssl AUC', '\\spexkge  [ITALIC] ssl APR', '\\spexkge  [ITALIC] ssl -  \\spexkge  [ITALIC] space ΔAUC', '\\spexkge  [ITALIC] ssl -  \\spexkge  [ITALIC] space ΔAPR']
We can see that \spexkgessl outperforms \spexkge′space with a significant margin (ΔAUC = 9.86% and ΔAPR = 9.59% on the testing dataset) which clearly shows the strength of considering both feature embedding and space embedding in spatial semantic lifting task.