This paper addresses the challenge of learning to do procedural reasoning over text to answer "What if..." questions. We propose a novel relational gating network that learns to filter the key entities and relationships and learns contextual and cross representations of both procedure and question for finding the answer. Our relational gating network contains an entity gating module, relation gating module, and contextual interaction module. These modules help in solving the "What if..." reasoning problem. We show that modeling pairwise relationships helps to capture higher-order relations and find the line of reasoning for causes and effects in the procedural descriptions. Our proposed approach achieves the state-of-the-art results on the WIQA dataset.

翻译：本文讨论了学习对文本进行程序性推理以回答“如果......会怎样”问题的挑战。 我们建议建立一个新的关系网, 以学习过滤关键实体和关系, 并学习对程序和问题的背景和交叉表达, 以找到答案。 我们的关系网包含一个实体标签模块, 关系标签模块, 和背景互动模块。 这些模块有助于解决“ 如果...” 推理问题。 我们显示, 建模双向关系有助于捕捉更高层次的关系, 并在程序描述中找到原因和效果的推理线。 我们提出的方法实现了WIQA数据集的最新结果 。