Such an approach is especially interesting either for lexicog-raphers aiming at constructing lexicons, but even more for natural language processing systems relying on deep lexical knowledge as represented by qualia structures.
we have focused on learning ranked qualia structures which allow to find an ideal cut-off point to increase the precision/recall trade-off of the learned structures.