In practice, the features automatically induced by NN are combined with the discrete features in the local approach to extend their coverage for EL (Sun et al., 2015;<cite> Francis-Landau et al., 2016)</cite> . However, as the previous NN models for EL are local, they cannot capture the global interdependence among the target entities in the same document (the first limitation of the local approach). Guided by these analyses, in this paper, we propose to use neural networks to model both the local mention-to-entity similarities and the global relatedness among target entities in an unified architecture. This allows us to inherit all the benefits from the previous systems as well as overcome their inherent issues.