Microsoft Technology Licensing, LLC

Benjamin Lev Snyder

Daniel Louis Klein

Adam David Pauls

Pengyu Chen

Benjamin David Van Durme

Jason Michael Eisner

Emmanouil Antonios Platanios

Samuel McIntire Thomson

Christopher H Lin

Subhro Roy

Eui Chul Shin

Systems and methods are provided for automatically generating a program based on a natural language utterance using semantic parsing. The semantic parsing includes translating a natural language utterance into instructions in a logical form for execution. The methods use a pre-trained natural language model and generate a canonical utterance as an intermediate form before generating the logical form. The natural language model may be an auto-regressive natural language model with a transformer to paraphrase a sequence of words or tokens in the natural language utterance. The methods generate a prompt including exemplar input/output pairs as a few-shot learning technique for the natural language model to predict words or tokens. The methods further use constrained decoding to determine a canonical utterance, iteratively selecting sequence of words as predicted by the model against rules for canonical utterances. The methods generate a program based on the canonical utterance for execution in an application.

Semantic parsing of utterance using contractive paraphrasing

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Bellevue, WA, United States of America

Benjamin Lev Snyder