Lifted first order and first order languages

I spent a week or two exploring first order and lifted first order languages. The idea is very simple; express models in first order, and the system creates the necessary graphical models to perform inference. From a machine learning perspective, this is a very useful idea. Since graphical models are not always in the repertoire of machine learners, this kind of first order language specification of probabilistic models will be advantageous. I think the eventual goal is to have such a system as a library to a standard programming platform, where the complexity of graphical models is abstracted away in the form of a blackbox.