Entity linking is the process of linking name mentions in text with their referent entities in a knowledge base. This paper tackles this task by proposing an approach based on topic-sensitive random walk with restart. Firstly, the context information of mentions is used to expand mentions and search the candidate entities in Wikipedia knowledge base for mentions. Secondly, graph can be constructed in accordance with the intermediate result in the pre step. Finally, the topic-sensitive random walk with restart model is used to rank the candidate entities and choose the top 1 as the linked entity. Experimental results show that proposed approach on KBP2014 data set gets F score 0.623 which is higher than every other systems' mentioned in this paper. The proposed approach can improve the entity linking system's performance.

An Entity Linking Approach Based on Topic-Sensitive Random Walk with Restart

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