Probabilistic inference will be of special importance when one needs to know how much we can say with what all we know given new observations. Bayesian Network is a graphical probabilistic model with which one can represent probabilistic relations intuitively and several effective algorithms for inference are developed. This paper reports a now ongoing work in its design stage which provides a vocabulary for representing probabilistic knowledge in a RDF graph which is to be mapped to a Bayesian Network to do inference on it.