Finally, we compared our algorithm with the reranking approach (Collins and Duffy, 2002;Collins, 2002b), where we first generate the n-best candidates using a model with only local features (the first model) and then re-rank the candidates using a model with non-local features (the second model).
cRFs or perceptrons generally have nearly zero error on the training data, although the first model should mis-label 11 The weights were re-trained for the second model.