Our work is an extension of<cite> (Francis-Landau et al., 2016)</cite> which only considers the local similarities. Given a document, we simultaneously perform linking for every entity mention from the beginning to the end of the document. For each entity mention, we utilize convolutional neural networks (CNN) to obtain the distributed representations for the entity mention as well as its target candidates. These distributed representations are then used for two purposes: (i) computing the local similarities for the entity mention and target candidates, and (ii) functioning as the input for the recurrent neural networks (RNN) that runs over the entity mentions in the documents.