In evaluation on two datasets, we show that: a) NBT models match the performance of delexicalisation-based models which make use of hand-crafted semantic lexicons; and b) the NBT models significantly outperform those models when such resources are not available.
we believe this work proposes a framework better-suited to scaling belief tracking models for deployment in real-world dialogue systems operating over sophisticated application domains where the creation of such domain-specific lexicons would be infeasible.