Aligning English Strings with Abstract Meaning Representation Graphs

Nima Pourdamghani, Yang Gao, Ulf Hermjakob, Kevin Knight

Abstract: We align pairs of English sentences and corresponding Abstract Meaning Representations (AMR), at the token level. Such alignments will be useful for downstream extraction of semantic interpretation and generation rules. Our method involves linearizing AMR structures and performing symmetrized EM training. We obtain 86.5% and 83.1% alignment F score on development and test sets.