Similar to Markov Logic Networks (MLNs) (Richardson and Domingos, 2006), it uses weighted first-order logic formulas to compactly encode complex undirected probabilistic graphical models.
for example, in the first sentence, He and hospital are the arguments, and in the second sentence, Aeroplanes and London are the fEs.