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.