Natural Language Reasoning based on Physical Constraints in the Real World

Abstract

This study aims to develop a method to predict physical events using language. It focuses on collisions between objects and takes into account their characteristics such as mass, speed, and environmental factors. Based on the CLEVRER dataset, this study creates a natural language dataset describing causal relationships in the physical environment. This dataset is used to infer the post-collision state of objects and express these predictions as natural language sentences. The study demonstrates that it is possible to predict events in the physical world using language, and to express these predictions as inferences in the symbolic world.