Abstract
Log-linear description logics are a family of prob-abilistic logics integrating various concepts and methods from the areas of knowledge representa-tion and reasoning and statistical relational AI. We define the syntax and semantics of log-linear de scription logics, describe a convenient represen-tation as sets of first-order formulas, and discuss computational and algorithmic aspects of proba-bilistic queries in the language. The paper con-cludes with an experimental evaluation of an im-plementation of a log-linear DL reasoner.