Otherwise, we update the weight vector in the Perceptron style, by promoting the features of the gold standard action, and demoting the features of the action of the top hypothesis.
then we re-generate the queue Q with P and the updated weight vector w. we first remove all the elements in Q, and then generate hypotheses for all the possible spans based on the context spans in P .