Identical molecules could play different roles depending of the relations they may have with different partners embedded in different processes, at different time and/or localization. To address such intricate networks that account for the complexity of living systems, systems biology is an emerging field that aims at understanding such dynamic interactions from the knowledge of their components and the relations between these components. Among main issues in system biology, knowledge on entities spatial relations is of importance to assess the topology of biological networks. In this perspective, mining data and texts could afford specific clues. To address this issue we examine the use of contextual exploration method to develop extraction rules that can retrieve information on relations between biological entities in scientific literature. We propose the system Seekbio that could be plugged at Pubmed output as an interface between results of PubMed query and articles selection following spatial relationships requests.