Specifically, approaches based on Markov Logic Networks (MLNs) (Richardson and Domingos, 2006) encode logical knowledge in dense, loopy graphical models, making structure learning, parameter estimation, and inference hard for the scale of our data.
in our model the logical knowledge is captured directly in the embeddings, leading to efficient inference.