The database in Artificial Research by Application

This paper focuses on the critical role of the database of words in the first stage—application—of Specific Artificial Intelligence (SAI) for Artificial Research by Application. Within this initial phase, the database functions as a structured repository of linguistic, conceptual, and categorical information relevant to a particular scientific or academic field. Words in the database are not merely stored as isolated entries but are indexed according to quantitative descriptors, taxonomic relations, functional uses, and semantic roles. The aim is to enable the SAI to interpret empirical inputs, categorize observed phenomena, and retrieve comparable entries that inform hypothesis formation. This process of word-based categorization allows the SAI to match new data with existing conceptual structures, serving as the foundation for replication by Application. In scientific contexts such as medicine or astronomy, this means associating terms (e.g., symptoms, physical properties, conditions) with standardized descriptions and quantitative attributes. The paper outlines the necessary structure of such a database, including multi-layered descriptors, synonym management, and relational hierarchies that allow words to function as gateways to rational hypothesis generation. Ultimately, this linguistic architecture provides a bridge between raw empirical data and structured reasoning, laying the groundwork for subsequent stages of artificial research.