Semantic parsing with semi-supervised sequential autoencoders

Semantic parsing with semi-supervised sequential autoencoders

We present a novel semi-supervised approach for sequence transduction and apply it to semantic parsing. The unsupervised component is based on a generative model in which latent sentences generate the unpaired logical forms. We apply this method to a number of semantic parsing tasks focusing on doma...

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Bibliografiske detaljer
Main Authors: Kočiský, T, Melis, G, Grefenstette, E, Dyer, C, Ling, W, Blunsom, P, Hermann, K
Format: Conference item
Udgivet: Association for Computational Linguistics 2016
Beskrivelse
Summary:We present a novel semi-supervised approach for sequence transduction and apply it to semantic parsing. The unsupervised component is based on a generative model in which latent sentences generate the unpaired logical forms. We apply this method to a number of semantic parsing tasks focusing on domains with limited access to labelled training data and extend those datasets with synthetically generated logical forms.

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