We start the training process by applying the rule INLINEFORM4 to a set of natural language questions INLINEFORM5 . The resulting dataset is considered as the training data to initialize both the semantic parser and the question generator. Afterwards, both models are improved following the back-translation protocol that target sequences should follow the real data distribution, yet source sequences can be generated with noises. 
 Question: How is the back-translation model trained?
 applying the rule INLINEFORM4 to a set of natural language questions INLINEFORM5 both models are improved following the back-translation protocol that target sequences should follow the real data distribution