Building Dynamic Knowledge Graphs from Text-based Games

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

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.