Reasoning about Goals, Steps, and Temporal Ordering with WikiHow
September 16, 2020 ยท Declared Dead ยท ๐ Conference on Empirical Methods in Natural Language Processing
"No code URL or promise found in abstract"
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Authors
Li Zhang, Qing Lyu, Chris Callison-Burch
arXiv ID
2009.07690
Category
cs.CL: Computation & Language
Citations
96
Venue
Conference on Empirical Methods in Natural Language Processing
Last Checked
4 months ago
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 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.
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