@InProceedings{hopkins-EtAl:2019:S19-2,
  author    = {Hopkins, Mark  and  Le Bras, Ronan  and  Petrescu-Prahova, Cristian  and  Stanovsky, Gabriel  and  Hajishirzi, Hannaneh  and  Koncel-Kedziorski, Rik},
  title     = {SemEval-2019 Task 10: Math Question Answering},
  booktitle = {Proceedings of the 13th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2019},
  address   = {Minneapolis, Minnesota, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {893--899},
  abstract  = {We report on the SemEval 2019 task on math question answering. We provided a question set derived from Math SAT practice exams, including 2778 training questions and 1082 test questions. For a significant subset of these questions, we also provided SMT-LIB logical form annotations and an interpreter that could solve these logical forms. Systems were evaluated based on the percentage of correctly answered questions. The top system correctly answered 45\% of the test questions, a considerable improvement over the 17\% random guessing baseline.},
  url       = {http://www.aclweb.org/anthology/S19-2153}
}