Abstract：Entity linking for knowledge base question answering is to link the entity mention in the natural language question to a target entity in the knowledge base. This paper employs the candidate entity's types, relationships and neighboring entities as the candidate entity representation, so as to solve the problem of insufficient description information of the entity in the knowledge base. At the same time, the similar entity mentions obtained by training the corpus are considered as the mention's background knowledge. Finally, the proposed features combine the entity popularity feature to solve the entity disambiguation problem. The experimental results on the data set show that the linear combination of all the above-mentioned features is better than the single feature.
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2019, Vol. 33 
