Microsoft Technology Licensing, LLC

Christopher H Lin

Daniel Louis Klein

Adam David Pauls

Pengyu Chen

Emmanouil Antonios Platanios

Jason Michael Eisner

Benjamin David Van Durme

Samuel McIntire Thomson

Subhro Roy

Benjamin Lev Snyder

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

Christopher H Lin