6. A method for natural language processing comprising steps of: receiving a natural language query; creating, by one or more processors, a query syntactic tree for the query; using, by one or more of the processors, a trained model comprising a model syntactic tree to predict if a node in the query syntactic tree is important, wherein the model syntactic tree comprises a syntactic parse tree of nodes representing syntactic elements of natural language input augmented with annotated important phrases, the model syntactic tree generated by at least creating a syntactic node, which augments the syntactic parse tree created by an information extraction pipeline for a named mention annotated as an important phrase, responsive to determining that no existing non-terminal nodes of the syntactic parse tree span exactly the named mention, wherein a semantic meaning of the natural language query is determined based on the model syntactic tree.
6. A method for natural language processing comprising steps of: receiving a natural language query; creating, by one or more processors, a query syntactic tree for the query; using, by one or more of the processors, a trained model comprising a model syntactic tree to predict if a node in the query syntactic tree is important, wherein the model syntactic tree comprises a syntactic parse tree of nodes representing syntactic elements of natural language input augmented with annotated important phrases, the model syntactic tree generated by at least creating a syntactic node, which augments the syntactic parse tree created by an information extraction pipeline for a named mention annotated as an important phrase, responsive to determining that no existing non-terminal nodes of the syntactic parse tree span exactly the named mention, wherein a semantic meaning of the natural language query is determined based on the model syntactic tree. 9. The method of claim 6 , further comprising assigning a score for each node in the query syntactic tree and generating bi-lexical dependencies between nodes.