(2008) took advantage of the hierarchical ontology of relations by proposing methods customized for the perceptron learning algorithm and support vector machines.
we propose a generic way of using the relation hierarchy which at the same time, gives globally coherent predictions and allows for easy injection of knowledge as constraints.