Combining word and entity embeddings for entity linking (ESWC 2017)
The general approach for the entity linking task is to generate, for a given mention, a set of candidate entities from the base and, in a second step, determine which is the best one. This paper proposes a novel method for the second step which is based on the **joint learning of embeddings for the words in the text and the entities in the knowledge base**.
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