Computer Science > Computation and Language
[Submitted on 1 Feb 2017 (v1), last revised 28 Apr 2017 (this version, v4)]
Title:AMR-to-text Generation with Synchronous Node Replacement Grammar
View PDFAbstract:This paper addresses the task of AMR-to-text generation by leveraging synchronous node replacement grammar. During training, graph-to-string rules are learned using a heuristic extraction algorithm. At test time, a graph transducer is applied to collapse input AMRs and generate output sentences. Evaluated on SemEval-2016 Task 8, our method gives a BLEU score of 25.62, which is the best reported so far.
Submission history
From: Linfeng Song [view email][v1] Wed, 1 Feb 2017 23:36:33 UTC (42 KB)
[v2] Tue, 7 Feb 2017 18:22:24 UTC (1 KB) (withdrawn)
[v3] Mon, 3 Apr 2017 02:39:14 UTC (42 KB)
[v4] Fri, 28 Apr 2017 13:37:00 UTC (78 KB)
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