An Interpretable Knowledge Transfer Model for Knowledge Base Completion
Table 2: Link prediction results on two datasets. Higher Hits@10 or lower Mean Rank indicates better performance. Following Nguyen et al. (2016b) and Shen et al. (2016), we divide the models into two groups. The first group contains intrinsic models without using extra information. The second group make use of additional information. Results in the brackets are another set of results STransE reported.
['[BOLD] Model', '[BOLD] Additional Information', '[BOLD] WN18 Mean Rank', '[BOLD] WN18 Hits@10', '[BOLD] FB15k Mean Rank', '[BOLD] FB15k Hits@10']
The overall link prediction results Our model consistently outperforms previous models without external information on both the metrics of WN18 and FB15k. On WN18, we even achieve a much better mean rank with comparable Hits@10 than current state-of-the-art model IRN employing external information.