The main contribution of this work is to tackle the WSC by: • developing and utilizing an automated knowledge hunting approach to extract the needed knowledge and reason with it without relying on a strict formal representation, • utilizing the knowledge that is embedded in the language models, and • combining the knowledge extracted from knowledge hunting and the knowledge in language models.
our approach improves on the existing state-of-the-art accuracy by 7.36% and solves 71.06% of the WSC problems correctly.