 Transformer-based language representation models, LIMs, have achieved state-of-the-art results on difficult natural language understanding problems, such as question-answering and text-summarization. As these models are integrated into real-world applications, evaluating their ability to make rational decisions is an important research agenda. This article was authored by Zhixing Tao and Mayank Kedruel.