Then we compute the probability that v belongs to C in WordNet given that (u, v) is an edge in the instance network and u belongs to C in WordNet: We compare this to the background probability P r b = Pr[v ∈ T C | u, v ∈ V and u ∈ T C ], which gives the probability that v belongs to C in WordNet if it is chosen at random.
if P r h = 1, this means that whenever u has the label C and (u, v) is an edge, then v is always labeled with C. If indeed this is the case, then a good classifier can simply take the initial set L and extend the labels to all nodes reachable from L in the semantic network.