THUNLP at TAC KBP 2011 in Entity Linking

Entity Linking is to link a name string from plain-text documents to the corresponding entry in given knowledge base. In this paper we demonstrate our entity linking system for TAC KBP 2011 Track. Our system implements pairwise and listwise learning to rank methods to create a ranking list of candidates with several kinds of features, including context similarity, term frequency, key entity extraction and WikiPage information. We participate in entity linking and cross-lingual entity linking task. We use random forest to validate the top 1 candidate recommended by our system. We achieve a performance of 72.9% F1 measure for both two tasks.