@inproceedings{gokcen-etal-2018-madly,
    title = "Madly Ambiguous: A Game for Learning about Structural Ambiguity and Why It{'}s Hard for Computers",
    author = "Gokcen, Ajda  and
      Hill, Ethan  and
      White, Michael",
    editor = "Liu, Yang  and
      Paek, Tim  and
      Patwardhan, Manasi",
    booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Demonstrations",
    month = jun,
    year = "2018",
    address = "New Orleans, Louisiana",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/N18-5011/",
    doi = "10.18653/v1/N18-5011",
    pages = "51--55",
    abstract = "Madly Ambiguous is an open source, online game aimed at teaching audiences of all ages about structural ambiguity and why it{'}s hard for computers. After a brief introduction to structural ambiguity, users are challenged to complete a sentence in a way that tricks the computer into guessing an incorrect interpretation. Behind the scenes are two different NLP-based methods for classifying the user{'}s input, one representative of classic rule-based approaches to disambiguation and the other representative of recent neural network approaches. Qualitative feedback from the system{'}s use in online, classroom, and science museum settings indicates that it is engaging and successful in conveying the intended take home messages. A demo of Madly Ambiguous can be played at \url{http://madlyambiguous.osu.edu}."
}