16. The method of claim 10 wherein the training data comprises semantically annotated training data and further comprising: accessing a probabilistic library grammar; and adapting probabilities in the probabilistic library grammar based on the semantically annotated training data.
10. A computer-implemented method of training a natural language understanding (NLU) model, comprising: obtaining a schema indicative of a task to be completed, the schema including a plurality of slots and a plurality of preterminals, wherein each of the plurality of slots is configured to be filled with terms from a natural language input that are associated with the task, and wherein each of the preterminals comprises at least one of a preamble and postamble associated with one or more of the slots, the preterminals being configured to be filled with portions of the natural language input; generating a plurality of segmentations of training data, for the plurality of slots and the plurality of preterminals from the schema, wherein generating a plurality of segmentations comprises associating one or more of the slots and one or more of the preterminals with portions of the training data; training a plurality of statistical models using a processor for selected preterminals of the plurality of preterminals corresponding to at least one of the segmentations, wherein the plurality of statistical models are configured to map terms from the natural language input to the selected preterminals, wherein training the plurality of statistical models comprises generating a statistical model for each of the plurality of selected preterminals comprising: selecting a first preterminal; generating a first statistical model for the selected first preterminal using the portion of the training data associated with the selected first preterminal as training data for the first statistical model; selecting a second preterminal; and generating a second statistical model for the selected second preterminal using the portion of the training data associated with the selected second preterminal as training data for the second statistical model; and training a rules based grammar using a processor for a selected slot of the plurality of slots corresponding to at least one of the segmentations, wherein the rules based grammar is configured to be used to map terms from the natural language input to the selected slot.