Paper: Aligning English Strings with Abstract Meaning Representation Graphs

ACL ID D14-1048
Title Aligning English Strings with Abstract Meaning Representation Graphs
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

Aligning English Strings with Abstract Meaning Representation Graphs Nima Pourdamghani, Yang Gao, Ulf Hermjakob, Kevin Knight Information Sciences Institute Department of Computer Science University of Southern California {damghani,yanggao,ulf,knight}@isi.edu Abstract We align pairs of English sentences and corresponding Abstract Meaning Repre- sentations (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 perform- ing symmetrized EM training. We obtain 86.5% and 83.1% alignment F score on de- velopment and test sets.