  An increasing number of entities are described by interlinked data rather
than documents on the Web. Entity Resolution (ER) aims to identify descriptions
of the same real-world entity within one or across knowledge bases in the Web
of data. To reduce the required number of pairwise comparisons among
descriptions, ER methods typically perform a pre-processing step, called
\emph{blocking}, which places similar entity descriptions into blocks and thus
only compare descriptions within the same block. We experimentally evaluate
several blocking methods proposed for the Web of data using real datasets,
whose characteristics significantly impact their effectiveness and efficiency.
The proposed experimental evaluation framework allows us to better understand
the characteristics of the missed matching entity descriptions and contrast
them with ground truth obtained from different kinds of relatedness links.
