Inspired by WLM, the KB graph model simply learns to place entities with similar incoming links near one another in the vector space.
we formalize this as the following objective function: we compute the conditional probability P (e o |e i ) using the following softmax function: we train the model to predict the incoming links C e given an entity e. C e plays a similar role to context words in the skip-gram model.