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The tasks of entity extraction, recognition, and linking are largely affected by the nature of the textual documents being analyzed. In fact, a lot of research efforts have focused on improving each task for both formal text (such as newswire documents) and for informal text (such as tweets). In this work, we propose a so-called hybrid approach that aims to be agnostic of the document type. Two datasets, namely the# Micropost2014 NEEL corpus and the OKE2015 test dataset, are used to benchmark the performance of our approach. The experimental results show that the approach presented in this paper outperforms the state-of-the-art systems on OKE2015 dataset and provides good results for the# Micropost2014 dataset.