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This paper addresses the task of AMR-to-text generation by leveragingsynchronous node replacement grammar. During training, graph-to-string rulesare learned using a heuristic extraction algorithm. At test time, a graphtransducer 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, whichis the best reported so far.

AMR-to-text Generation with Synchronous Node Replacement Grammar