Now, define a new training set of the form .
that is, t is identical to t, except that each training input x is augmented with the cross-validation prediction of model C. Finally, let this means that, for every sentence x ∈ t, B C has access at training time to both the gold standard dependency graph G x and the graph G C x predicted by C. B C is able to define guide features over G C x , which can prove beneficial if features over G C x can be used to discern when parsing model C outperforms or underperforms parsing model B.