  In this paper a new proof is given for the supermodularity of information
content. Using the decomposability of the information content an algorithm is
given for discovering the Markov network graph structure endowed by the
pairwise Markov property of a given probability distribution. A discrete
probability distribution is given for which the equivalence of
Hammersley-Clifford theorem is fulfilled although some of the possible vector
realizations are taken on with zero probability. Our algorithm for discovering
the pairwise Markov network is illustrated on this example, too.
