8. The method of claim 5 and further comprising: training the NLU system with the verified annotations.
5. A method, performed using one or more processors, of generating annotated training data for training a natural language understanding (NLU) system, comprising: generating, with the NLU system running on one or more of the processors, a proposed annotation for each of a plurality of units of unannotated training data, each proposed annotation having a semantic type; displaying on an output component at least some of the proposed annotations in an order based on the semantic type of each of the proposed annotations, with one or more input components providing one or more user-actuable inputs configured for verification of the proposed annotations and one or more user-actuable inputs configured for deletion of the proposed annotations; when an input for verification is received, responding, with one or more of the processors, to the input for verification of one of the proposed annotations by storing the verified annotation for the given unit of the training data; and when an input for deletion is received, responding, with one or more of the processors, to the input for deletion of one of the proposed annotations by presenting at least some of the remaining proposed annotations in an order based on the semantic type of each of the remaining proposed annotations.