Semantic Category Analysis of Poetry and Prose

The human mind creates and interprets beautiful literature. Perhaps one of the greatest challenges for Machine Intelligence is the replication of those skills. `Semantic Category Theory´ indicates that human language cognition is based upon four distinct data types that can be combined in one of two ways. The analytical adjunct to Semantic Category Theory, `Semantic Category Analysis´, determines the specific data types and interaction modes involved in any spoken or written text. This paper illustrates the Semantic Category Analysis of human-created Poetry and Prose. The paper further demonstrates how the tenets of Semantic Category Theory form a basis for the Machine-creation of Poetry and Prose; a requisite for comprehensive Human-Machine dialogue.