Traversing Knowledge Graphs in Vector Space
Table 5: Model performance in terms of accuracy. EV: entity vectors are separate (initialized randomly); WV: entity vectors are average of word vectors (initialized with pretrained word vectors).
['Accuracy', '[BOLD] WordNet EV', '[BOLD] WordNet WV', '[BOLD] Freebase EV', '[BOLD] Freebase WV']
We initialized all models with word vectors from \newcitepennington2014glove. We found that compositionally trained models outperform the neural tensor network (NTN) on WordNet, while being only slightly behind on Freebase. (We did not use word vectors in any of our other experiments.)