15. A method of utilizing an information extraction system to extract information from a natural language input, comprising: receiving a natural language input; utilizing a computer processor, that is a component of a computer, to generate a set of parses from the natural language input based on a template indicative of information to be extracted from the natural language input, wherein the set of parses are generated using a structured language model trained by generating a set of syntactic parses for a given word string that all match semantic constituent boundaries, by determining whether unlabeled constituents that define a semantic parse is included in a set of constituents that define the syntactic parse, wherein parses that do not match the semantic constituent boundaries are discarded, and replacing syntactic labels in a parse tree with joint syntactic and semantic labels based on the generated parses excluding the discarded parses, and retraining the structured language model by generating parses that are constrained to identically match the semantic constituent labels of the joint syntactic and semantic labels and constrained to match all of the semantic constituent boundaries; calculating a probability for each of the generated parses, comprising summing the probability over all parses having a common semantic parse; ranking the set of parses based on the probability; and outputting one or more of the parses based on the ranking.
15. A method of utilizing an information extraction system to extract information from a natural language input, comprising: receiving a natural language input; utilizing a computer processor, that is a component of a computer, to generate a set of parses from the natural language input based on a template indicative of information to be extracted from the natural language input, wherein the set of parses are generated using a structured language model trained by generating a set of syntactic parses for a given word string that all match semantic constituent boundaries, by determining whether unlabeled constituents that define a semantic parse is included in a set of constituents that define the syntactic parse, wherein parses that do not match the semantic constituent boundaries are discarded, and replacing syntactic labels in a parse tree with joint syntactic and semantic labels based on the generated parses excluding the discarded parses, and retraining the structured language model by generating parses that are constrained to identically match the semantic constituent labels of the joint syntactic and semantic labels and constrained to match all of the semantic constituent boundaries; calculating a probability for each of the generated parses, comprising summing the probability over all parses having a common semantic parse; ranking the set of parses based on the probability; and outputting one or more of the parses based on the ranking. 19. The method of claim 15 , wherein parsing the natural language input comprises: associating headwords with nodes in a syntactic parse; and enforcing the syntactic parse to match a label constraint.