Named entity linking systems are an essential component in text mining pipelines, mapping entity mentions in the text to the appropriate knowledge base identifiers. However, the current systems have several limitations affecting their performance: the lack of context of the entity mentions, the incomplete disambiguation graphs and the lack of approaches to deal with unlinkable entity mentions. The PhD project will focus on solving the aforementioned challenges in order to develop a NEL model which outperforms state-of-the-art performance in Biomedical and Life Sciences domains.