Disentangling Language and Knowledge in Task-Oriented Dialogs
Table 2: Performance of BoSsNet and baselines on the CamRest and SMD datasets
['[EMPTY]', '[BOLD] CamRest  [BOLD] BLEU', '[BOLD] CamRest  [BOLD] Ent. F1', '[BOLD] SMD  [BOLD] BLEU', '[BOLD] SMD  [BOLD] Ent. F1']
BoSsNet greatly outperforms other models in both Entity F1 metric and BLEU scores on CamRest. On SMD, BoSsNet achieves the best only in Entity F1. On further analysis of the generated responses we observe that BoSsNet responses often convey the necessary entity information from the KB. However, they consist of meaningful phrases with little lexical overlap with the gold response, reducing the BLEU scores. We investigate this further in our human evaluation.