@inproceedings{li-etal-2017-guess,
    title = "Guess What: A Question Answering Game via On-demand Knowledge Validation",
    author = "Li, Yu-Sheng  and
      Tseng, Chien-Hui  and
      Huang, Chian-Yun  and
      Ma, Wei-Yun",
    editor = "Park, Seong-Bae  and
      Supnithi, Thepchai",
    booktitle = "Proceedings of the {IJCNLP} 2017, System Demonstrations",
    month = nov,
    year = "2017",
    address = "Tapei, Taiwan",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/I17-3015/",
    pages = "57--60",
    abstract = "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."
}