Formally, let W be the vocabulary set containing n words w 1 , w 2 , ..., w n and R the relations set containing m relations r 1 , r 2 , ..., r m , the proposed model is expected to produce m + 1 embeddings for each word, where there are m relational embeddings representing relations and a center em-bedding c for the general semantics.
each relational embedding has an overall and a local version, denoted as v and u, where u records the difference between v and c. For both the relational embeddings (v and u) and the center embedding, we use a similar way as that in word2vec (Mikolov et al., 2013) that each one has two variants to represent the semantics of a word w being the head or tail in different relations.