Generating Logical Forms from Graph Representations of Text and Entities

Peter Shaw; Philip Massey; Angelica Chen; Francesco Piccinno; Yasemin Altun

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arXiv · 1905.08407

Generating Logical Forms from Graph Representations of Text and Entities

Peter Shaw·Philip Massey·Angelica Chen·Francesco Piccinno·Yasemin Altun

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Abstract

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 state-of-the-art across several tasks without pre-training, and outperforms existing approaches when combined with BERT pre-training.

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Peter Shaw, Philip Massey, Angelica Chen, Francesco Piccinno, Yasemin Altun. 2019-05-21. Generating Logical Forms from Graph Representations of Text and Entities. https://arxiv.org/abs/1905.08407

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