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Weasel: a Machine Learning Based Approach to Entity Linking combining different features

The task of entity linking consists in disambiguating named entities occurring in textual data by linking them to an identifier in a knowledge base that represents the real-world entity they denote. We present Weasel, a novel approach that is based on a combination of different features that is trained using a Support Vector Machine. We compare our approach to state-of-the-art tools such as FOX and DBpedia spotlight, showing that it outperforms both on the AIDA/CoNLL dataset and provides comparable results on the KORE50 dataset.