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With the increasing number of communication platforms that offer variety of ways of connecting two interlocutors, there is a resurgence of chat-based dialog systems. These systems, typically known as chatbots have been successfully applied in a range of consumer and enterprise applications. A key technology in such chat-bots is robust natural language understanding (NLU) which can significantly influence and impact the efficacy of the conversation and ultimately the user-experience. While NLU is far from perfect, this paper illustrates the role of underspecification and its impact on successful dialog completion.

Underspecification in Natural Language Understanding for Dialog Automation