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Given a source document with extracted mentions,entity linking callsfor map-ping the mention to an entity in reference knowledge base.Previous en-tity linking approaches mainly focus on generic statistic features to link mentions independently.However,additional interdependence among mentions in the same document achieved from relational analysis can improve the accuracy.This paper propose a collective entity linking model which effectively leverages the global interdependence among mentions in the same source document.The model unifies semantic relations and co-reference relations into relational infer-ence for se-mantic information extraction.Graph based linking algorithm is uti-lized to ensure per mention with only one candidate entity.Experiments on da-tasets show the proposed model significantly out-performs the state-of-the-art re-latedness approaches in term of accuracy.