This graphic model views the paths as discrete latent variables and relation as the observed variables with a given entity pair as the condition, thus the path-finding module can be viewed as a prior distribution to infer the underlying links in the KG.
during testing, we use a beam of 5 to approximate the whole search space for path finder.