@conference {2583, title = {Learning to Answer Questions from Wikipedia Infoboxes}, booktitle = {The 2016 Conference on Empirical Methods on Natural Language Processing (EMNLP 2016)}, year = {2016}, abstract = {
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{\textemdash}infoboxes\ in Wikipedia that summarize factoid knowledge{\textemdash}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.
}, author = {Alvaro Morales and Varot Premtoon and Cordelia Avery and Sue Felshin and Boris Katz} }