A standard pipeline for statistical relational learning involves two steps: one first constructs the knowledge base (KB) from text, and then performs the learning and reasoning tasks using probabilistic first-order logics.
a key issue is that information extraction (IE) errors from text affect the quality of the KB, and propagate to the reasoning task.