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arXiv:1910.09532cs.CL

Building Dynamic Knowledge Graphs from Text-based Games

Mikuláš Zelinka, Xingdi Yuan, Marc-Alexandre Côté, Romain Laroche, Adam Trischler

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Abstract

We are interested in learning how to update Knowledge Graphs (KG) from text. In this preliminary work, we propose a novel Sequence-to-Sequence (Seq2Seq) architecture to generate elementary KG operations. Furthermore, we introduce a new dataset for KG extraction built upon text-based game transitions (over 300k data points). We conduct experiments and discuss the results.

arXiv comments
NeurIPS 2019, Graph Representation Learning (GRL) Workshop
Journal reference
DOI
Subjects
cs.CLComputation and Language cs.LGMachine Learning

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