Before revision: This paper presents a methodology and toolkit for creating a rule-based multi-domain conversational agent for transactions from (1) language annotations of the domains' database schemas and APIs and (2) a couple of hundreds of annotated human dialogues. There is no need for a large annotated training set , which is expensive to acquire.
After revision: The traditional dialogue state tracking (DST) task tracks the dialogue state given the past history of user and agent utterances. This paper proposes to replace the utterances before the current turn with a formal representation , which is expensive to acquire.