Semantics as a Foreign Language

Gabriel Stanovsky, Ido Dagan
2018 Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing  
We propose a novel approach to semantic dependency parsing (SDP) by casting the task as an instance of multi-lingual machine translation, where each semantic representation is a different foreign dialect. To that end, we first generalize syntactic linearization techniques to account for the richer semantic dependency graph structure. Following, we design a neural sequence-to-sequence framework which can effectively recover our graph linearizations, performing almost on-par with previous SDP
more » ... e-of-the-art while requiring less parallel training annotations. Beyond SDP, our linearization technique opens the door to integration of graph-based semantic representations as features in neural models for downstream applications.
doi:10.18653/v1/d18-1263 dblp:conf/emnlp/StanovskyD18 fatcat:4blyps4sx5efxnn4tfc5o4fvz4