Link prediction in a network is mostly based on information about the neighborhood topology of the nodes. Recently, the interest for hybrid link prediction approaches that combine topology information with information about the network individuals, has grown. However, considering the whole set of individuals may not be necessary and sometimes not even suitable. Therefore, mechanisms to automatically discover the relevant set of individuals are demanding. In this paper, we encompass this problem by proposing an algorithm that combines structure and semantic metrics to find the set of relevant individuals. We empirically evaluate this proposal analyzing the assertion role of these individuals when predicting a link through a probabilistic ontology.