We create 17 binary features, 16 of which correspond to the 16 IS subtypes and the remaining one corresponds to a "dummy subtype".
if the NP un-der consideration appears in the training set, we use Rule 17 in our hand-crafted ruleset to determine the IS subtype it is most frequently associated with in the training set, and then set the value of the feature corresponding to this IS subtype to 1.