Abstract

We present a method for generating English sentences from Abstract Meaning Representation (AMR) graphs, exploiting a parallel corpus of AMRs and English sentences. We treat AMR-to-English generation as phrase-based machine translation (PBMT). We introduce a method that learns to linearize tokens of AMR graphs into an English-like order. Our linearization reduces the amount of distortion in PBMT and increases generation quality. We report a Bleu score of 26.8 on the standard AMR/English test set.

Date

March 12, 2026

Authors

Nima Pourdamghani, Kevin Knight, Ulf Hermjakob

Conference

Proceedings of the 9th international natural language generation conference

Pages

21-25