NOTE: BLOG has been moved to the new homepage: http://bayesianlogic.cs.berkeley.edu
Bayesian Logic (BLOG) is a first-order probabilistic modeling language under development at UC Berkeley. It is designed for making inferences about real-world objects that underlie some observed data: for instance, tracking multiple people in a video sequence, or identifying repeated mentions of people and organizations in a set of text documents. BLOG makes it relatively easy to represent uncertainty about the number of underlying objects and the mapping between objects and observations.
The language reference for this version can be downloaded from EECS-2013-51