  Wikipedia, the largest open-collaborative online encyclopedia, is a corpus of
documents bound together by internal hyperlinks. These links form the building
blocks of a large network whose structure contains important information on the
concepts covered in this encyclopedia. The presence of a link between two
articles, materialised by an anchor text in the source page pointing to the
target page, can increase readers' understanding of a topic. However, the
process of linking follows specific editorial rules to avoid both under-linking
and over-linking. In this paper, we study the transductive and the inductive
tasks of link prediction on several subsets of the English Wikipedia and
identify some key challenges behind automatic linking based on anchor text
information. We propose an appropriate evaluation sampling methodology and
compare several algorithms. Moreover, we propose baseline models that provide a
good estimation of the overall difficulty of the tasks.
