Abstract:
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.
