How does Scallop scale on large knowledge bases (KBs) for doing probabilistic reasoning? I'm currently working on large KB with ~ 12M facts and trying to do probabilistic inference on it. So far I've been using [cplint](https://friguzzi.github.io/cplint/_build/html/index.html) which is based on SWI-Prolog. It works fine for toy examples, however, it doesn't finish running for the large KB - even after waiting for it for more than a week. Does know any Probabilistic Logic Programming (PLP) libraries that are fast and scale to large KBs? Preferably in Prolog ecosystem, but not a hard requirement.