  Semantic parsing is challenging due to the structure gap and the semantic gap
between utterances and logical forms. In this paper, we propose an unsupervised
semantic parsing method - Synchronous Semantic Decoding (SSD), which can
simultaneously resolve the semantic gap and the structure gap by jointly
leveraging paraphrasing and grammar constrained decoding. Specifically, we
reformulate semantic parsing as a constrained paraphrasing problem: given an
utterance, our model synchronously generates its canonical utterance and
meaning representation. During synchronous decoding: the utterance paraphrasing
is constrained by the structure of the logical form, therefore the canonical
utterance can be paraphrased controlledly; the semantic decoding is guided by
the semantics of the canonical utterance, therefore its logical form can be
generated unsupervisedly. Experimental results show that SSD is a promising
approach and can achieve competitive unsupervised semantic parsing performance
on multiple datasets.
