We encode domain knowledge as First Order Logic (FOL) rules and automatically integrate them with a topic model to produce clusters shaped by the data and the constraints at hand.
we extend the Fold-all (First-Order Logic latent Dirichlet Allocation) framework (Andrzejewski et al., 2011) to the relation extraction task, explain how to incorporate meaningful constraints, and develop a scalable inference technique.