To address the problem of learning relational knowledge, as shown in (Lin et al., 2016;Ye et al., 2017), we use class embeddings to represent relation classes and utilize KG embeddings and graph convolution networks (GCNs) to extract implicit and explicit relational knowledge.
previous studies  have shown that the embeddings of semantically similar relations are located near each other in the latent space.