Factorising AMR generation through syntax

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• Kris Cao, DeepMind
• Friday 10 May 2019, 12:00-13:00
• FW26, Computer Laboratory.

If you have a question about this talk, please contact Andrew Caines.

Generating from Abstract Meaning Representation (AMR) is an underspecified problem, as many syntactic decisions are not constrained by the semantic graph. To explicitly account for this underspecification, we break down generating from AMR into two steps: first generate a syntactic structure, and then generate the surface form. We show that decomposing the generation process this way leads to state-of-the-art single model performance generating from AMR without additional unlabelled data. We also demonstrate that we can generate meaning-preserving syntactic paraphrases of the same AMR graph, as judged by humans.

This talk is part of the NLIP Seminar Series series.

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