%0 Conference Proceedings %T Reasoning about Goals, Steps, and Temporal Ordering with WikiHow %A Zhang, Li %A Lyu, Qing %A Callison-Burch, Chris %Y Webber, Bonnie %Y Cohn, Trevor %Y He, Yulan %Y Liu, Yang %S Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) %D 2020 %8 November %I Association for Computational Linguistics %C Online %F zhang-etal-2020-reasoning %X We propose a suite of reasoning tasks on two types of relations between procedural events: goal-step relations (“learn poses” is a step in the larger goal of “doing yoga”) and step-step temporal relations (“buy a yoga mat” typically precedes “learn poses”). We introduce a dataset targeting these two relations based on wikiHow, a website of instructional how-to articles. Our human-validated test set serves as a reliable benchmark for common-sense inference, with a gap of about 10% to 20% between the performance of state-of-the-art transformer models and human performance. Our automatically-generated training set allows models to effectively transfer to out-of-domain tasks requiring knowledge of procedural events, with greatly improved performances on SWAG, Snips, and Story Cloze Test in zero- and few-shot settings. %R 10.18653/v1/2020.emnlp-main.374 %U https://aclanthology.org/2020.emnlp-main.374 %U https://doi.org/10.18653/v1/2020.emnlp-main.374 %P 4630-4639