Again, the loss function is a function of the margins on training data: Note the similarity of equation 10to the ExpLoss function for classification in equation (6).
for each k we define the following sets: A + k is the set of training examples in which the kth feature is seen in the correct parse but not in the competing parse; A À k is the set in which the kth feature is seen in the incorrect but not the correct parse.