Abstract

We present a parser for Abstract Meaning Representation (AMR). We treat Englishto-AMR conversion within the framework of string-to-tree, syntax-based machine translation (SBMT). To make this work, we transform the AMR structure into a form suitable for the mechanics of SBMT and useful for modeling. We introduce an AMR-specific language model and add data and features drawn from semantic resources. Our resulting AMR parser significantly improves upon state-of-the-art results.

Date

January 1, 1970

Authors

Michael Pust, Ulf Hermjakob, Kevin Knight, Daniel Marcu, Jonathan May

Conference

Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

Pages

1143-1154