Generating Logical Forms from Graph Representations of Text and Entities

Peter Shaw, Philip Massey, Angelica Chen, Francesco Piccinno, Yasemin Altun
2019 Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics  
Structured information about entities is critical for many semantic parsing tasks. We present an approach that uses a Graph Neural Network (GNN) architecture to incorporate information about relevant entities and their relations during parsing. Combined with a decoder copy mechanism, this approach provides a conceptually simple mechanism to generate logical forms with entities. We demonstrate that this approach is competitive with the stateof-the-art across several tasks without pretraining,
more » ... out pretraining, and outperforms existing approaches when combined with BERT pre-training.
doi:10.18653/v1/p19-1010 dblp:conf/acl/ShawMCPA19 fatcat:nd2ayfiqcnhu7pbcsbnnvlrbcq