Reviews: SimplE Embedding for Link Prediction in Knowledge Graphs

The contribution is a tensor factorization method that represents each object and relation as some vector. The main novelty relative to previous approaches is that each relation r is represented by two embedding vectors: one for r, and one for r -1. The motivation is that should allow objects that appear as both heads and tails to more easily learn jointly from both roles.