Neural Semantic Parsing

Matt Gardner, Pradeep Dasigi, Srinivasan Iyer, Alane Suhr, Luke Zettlemoyer


Abstract
Semantic parsing, the study of translating natural language utterances into machine-executable programs, is a well-established research area and has applications in question answering, instruction following, voice assistants, and code generation. In the last two years, the models used for semantic parsing have changed dramatically with the introduction of neural encoder-decoder methods that allow us to rethink many of the previous assumptions underlying semantic parsing. We aim to inform those already interested in semantic parsing research of these new developments in the field, as well as introduce the topic as an exciting research area to those who are unfamiliar with it. Current approaches for neural semantic parsing share several similarities with neural machine translation, but the key difference between the two fields is that semantic parsing translates natural language into a formal language, while machine translation translates it into a different natural language. The formal language used in semantic parsing allows for constrained decoding, where the model is constrained to only produce outputs that are valid formal statements. We will describe the various approaches researchers have taken to do this. We will also discuss the choice of formal languages used by semantic parsers, and describe why much recent work has chosen to use standard programming languages instead of more linguistically-motivated representations. We will then describe a particularly challenging setting for semantic parsing, where there is additional context or interaction that the parser must take into account when translating natural language to formal language, and give an overview of recent work in this direction. Finally, we will introduce some tools available in AllenNLP for doing semantic parsing research.
Anthology ID:
P18-5006
Volume:
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts
Month:
July
Year:
2018
Address:
Melbourne, Australia
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
17–18
Language:
URL:
https://aclanthology.org/P18-5006
DOI:
10.18653/v1/P18-5006
Bibkey:
Cite (ACL):
Matt Gardner, Pradeep Dasigi, Srinivasan Iyer, Alane Suhr, and Luke Zettlemoyer. 2018. Neural Semantic Parsing. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts, pages 17–18, Melbourne, Australia. Association for Computational Linguistics.
Cite (Informal):
Neural Semantic Parsing (Gardner et al., ACL 2018)
Copy Citation:
PDF:
https://aclanthology.org/P18-5006.pdf