Later work by <cite>Wang et al. (2015b)</cite> adopted a different strategy based on the similarity between the dependency parse of a sentence and the semantic AMR graph. To learn the parser, <cite>Wang et al. (2015b)</cite> define an algorithm that for each instance in the training data infers the action sequence that convert the input dependency tree into the corresponding AMR graph and train a classifier to predict the actions to be taken during testing.