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Task-oriented conversational agents rely on semantic parsers to translatenatural language to formal representations. In this paper, we propose thedesign and rationale of the ThingTalk formal representation, and how the designimproves the development of transactional task-oriented agents.  ThingTalk is built on four core principles: (1) representing user requestsdirectly as executable statements, covering all the functionality of the agent,(2) representing dialogues formally and succinctly to support accuratecontextual semantic parsing, (3) standardizing types and interfaces to maximizereuse between agents, and (4) allowing multiple, independently-developed agentsto be composed in a single virtual assistant. ThingTalk is developed as part ofthe Genie Framework that allows developers to quickly build transactionalagents given a database and APIs.  We compare ThingTalk to existing representations: SMCalFlow, SGD, TreeDST.Compared to the others, the ThingTalk design is both more general and morecost-effective. Evaluated on the MultiWOZ benchmark, using ThingTalk andassociated tools yields a new state of the art accuracy of 79% turn-by-turn.

ThingTalk: An Extensible, Executable Representation Language for Task-Oriented Dialogues