Logic and probability are ancient subjects whose unification holds significant potential for the field of artificial intelligence. The BLOG (Bayesian LOGic) language provides a way to write probability models using syntactic and semantic devices from first-order logic. In modern parlance, it is a relational, open-universe probabilistic programming language that allows one to define probability distributions over the entire space of first-order model structures that can be constructed given the constant, function, and predicate symbols of the program. I will describe the language mainly through examples and cover its application to monitoring the Comprehensive Nuclear-Test-Ban Treaty.