%0 Conference Paper %B The 2016 Conference on Empirical Methods on Natural Language Processing (EMNLP 2016) %D 2016 %T Learning to Answer Questions from Wikipedia Infoboxes %A Alvaro Morales %A Varot Premtoon %A Cordelia Avery %A Sue Felshin %A Boris Katz %X
A natural language interface to answers on the Web can help us access information more ef- ficiently. We start with an interesting source of information—infoboxes in Wikipedia that summarize factoid knowledge—and develop a comprehensive approach to answering ques- tions with high precision. We first build a system to access data in infoboxes in a struc- tured manner. We use our system to construct a crowdsourced dataset of over 15,000 high- quality, diverse questions. With these ques- tions, we train a convolutional neural network model that outperforms models that achieve top results in similar answer selection tasks.
%B The 2016 Conference on Empirical Methods on Natural Language Processing (EMNLP 2016) %G eng