Ethan Hill


Madly Ambiguous: A Game for Learning about Structural Ambiguity and Why It’s Hard for Computers
Ajda Gokcen | Ethan Hill | Michael White
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations

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


Generating Disambiguating Paraphrases for Structurally Ambiguous Sentences
Manjuan Duan | Ethan Hill | Michael White
Proceedings of the 10th Linguistic Annotation Workshop held in conjunction with ACL 2016 (LAW-X 2016)