A Hybrid Re-ranking Method for Entity Recognition and Linking in Search Queries

In this paper, we construct an entity recognition and linking system using Chinese Wikipedia and knowledge base. We utilize refined filter rules in entity recognition module, and then generate candidate entities by search engine and attributes in Wikipedia article pages. In entity linking module, we propose a hybrid entity re-ranking method combined with three features: textual and semantic match-degree, the similarity between candidate entity and entity mention, entity frequency. Finally, we get the linking results by the entity's final score. In the task of entity recognition and linking in search queries at NLPCC 2015, the Average-F1 value of this method achieved 61.1% in 3849 test dataset, which ranks second place in fourteen teams.