@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} }