Emerging Entity Discovery Using Web Sources

Lei Zhang, Tianxing Wu, Liang Xu, Meng Wang, Guilin Qi, Harald Sack

Abstract: The rapidly increasing amount of entities in knowledge bases (KBs) can be beneficial for many applications, where the key issue is to link entity mentions in text with entities in the KB, also called entity linking (EL). Many methods have been proposed to tackle this problem. However, the KB can never be complete, such that emerging entity discovery (EED) is essential for detecting emerging entities (EEs) that are mentioned in text but not yet contained in the KB. In this paper, we propose a new topic-driven approach to EED by representing EEs using the context harvested from online Web sources. Experimental results show that our solution outperforms the state-of-the-art methods in terms of F1 measure for the EED task as well as Micro Accuracy and Macro Accuracy in the full EL setting.