We propose novel approaches for two sub-tasks of the problem: identifying the entities of interest, and partitioning and describing the relations based on their semantics.
we show that term frequency patterns can be used effectively instead of supervised NER, and that the pmedian clustering objective function naturally uncovers relation exemplars appropriate for describing the partitioning.