  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 commonsense
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 the Story Cloze Test in zero- and
few-shot settings.
