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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 pro

by xabush 1y ago

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 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.

nextos 1y ago
ProbLog? https://dtai.cs.kuleuven.be/problog https://dtai.cs.kuleuven.be/problog
riku_iki 1y ago
I am surprised you have problems with 12M facts and can't process them in a week, looks like bug in software you are using.
- xabush 1y ago
  Thanks for the comment. Have you run cplint on a kb of the similar size before and gotten it to finish in reasonable time?
  - riku_iki 1y ago
    I never used cplint, but I use other software (including I built myself) to process KBs with many billions of facts.
    - xabush 1y ago
      Is the software open-source? If so, can you share a link to it?