Each classifier was trained per relation as in the previous experiments, but this time as negative examples we considered only those belonging to the corresponding contingency set.
we split the 1,000 example corpus into three datasets corresponding to the following contingency sets: {Component-Integral, Origin-Entity, Purpose}, {Content-Container, Measure/Content-Container, P-Whp/Measure/Content-Container}, and {P-Whp/Measure, Measure, P-Whp}.