1. A method comprising: collecting a plurality of task-oriented, human-human dialog interactions between users and human agents for a given domain; after collecting the plurality of task-oriented, human-human dialog interactions, extracting, via a processor, a respective dialog structure associated with each of the plurality of task-oriented, human-human dialog interactions, wherein extracting the respective dialog structure comprises: identifying a respective task in each of the plurality of task-oriented, human-human dialog interactions; identifying subtasks in the respective task and associating relations between the subtasks, wherein the identifying of the subtask is done using a chunk model equation PT*=argmax Σ ST P(ST|U)P(PT|ST), where PT* is the most likely plan tree, ST is each subtask in a sequence of utterances U, PT represents likelihood of each plan tree, and P represents the individual probabilities within the chunk model equation, where the chunk model equation uses the respective dialog structures U and ST as a weighted lattice; and identifying a dialog act and a set of predicate-argument relations for the subtasks by annotating user utterances in the plurality of task-oriented, human-human dialog interactions with tags; generating a clause from the set of predicate-argument relations; removing speech repairs and dysfluencies from a respective user utterance in each of the plurality of task-oriented, human-human dialog interactions; and storing the respective task, the subtasks, the dialog act, the set of predicate-argument relations, the clause, inter-clausal relations within the clause, and a set of dominance and precedence relations associated with the respective task as a dialog interaction set represented as a single tree.