Our problem therefore becomes one of identifying the posterior distribution of e given t, which we can do using Bayes' Rule: Since the sequence of elementary trees can be split into derivations, each of which completely specifies a tree, P (t|e) is either equal to 1 (when t and e are consistent) or 0 (otherwise).
the work in our model is done by the prior distribution over elementary trees.