1. A method for creating training data for a natural language processing system comprising: obtaining natural language input, the natural language input annotated with one or more important phrases; generating, by a processor, training instances comprising a syntactic parse tree of nodes representing elements of the natural language input augmented with the annotated important phrases, the generating comprising at least creating a syntactic node, which augments the syntactic parse tree output by an information extraction pipeline, for a named mention annotated as an important phrase, responsive to determining that no existing non-terminal nodes in the syntactic parse tree span exactly the named mention; and training a classifier based on the generated training instances, wherein the natural language processing system executes the classifier in determining a semantic meaning of a given query.