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Guess What: A Question Answering Game via On-demand Knowledge Validation

2017-11-01 · IJCNLP 2017 11 · Yu-Sheng Li, Chien-Hui Tseng, Chian-Yun Huang, Wei-Yun Ma

In this paper, we propose an idea of ondemand knowledge validation and fulfill the idea through an interactive Question-Answering (QA) game system, which is named Guess What. An object (e.g. dog) is first randomly chosen by the system, and then a user can repeatedly ask the system questions in natural language to guess what the object is. The system would respond with yes/no along with a confidence score. Some useful hints can also be given if needed. The proposed framework provides a pioneering example of on-demand knowledge validation in dialog environment to address such needs in AI agents/chatbots. Moreover, the released log data that the system gathered can be used to identify the most critical concepts/attributes of an existing knowledge base, which reflects human{'}s cognition about the world.

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ChatbotQuestion Answering

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