HIT Approaches to Entity Linking at TAC 2011

Knowledge Base Population (KBP) track En-glish Entity Linking task. Based on structured and unstructured information extracted from Wikipedia, this system predicts the most prob-able entity that a query mention might refer to. A similarity score is assigned to the candidate entity by computing the the relatedness be-tween the query and the entity, and augmented by the popularity of the entity. We model the query context as a graph of the entities and u-tilize the referential relationship between the context entities and the candidate entities in Wikipedia to measure the relatedness between the query context and the candidate entity. E-valuation results show the performance of ou