  Motivations, emotions, and actions are inter-related essential factors in
human activities. While motivations and emotions have long been considered at
the core of exploring how people take actions in human activities, there has
been relatively little research supporting analyzing the relationship between
human mental states and actions. We present the first study that investigates
the viability of modeling motivations, emotions, and actions in language-based
human activities, named COMMA (Cognitive Framework of Human Activities). Guided
by COMMA, we define three natural language processing tasks (emotion
understanding, motivation understanding and conditioned action generation), and
build a challenging dataset Hail through automatically extracting samples from
Story Commonsense. Experimental results on NLP applications prove the
effectiveness of modeling the relationship. Furthermore, our models inspired by
COMMA can better reveal the essential relationship among motivations, emotions
and actions than existing methods.
