Ontologies are equally important, as they represent the backbone of the formal semantics of a knowledge graph. As the data schema of the graph, they serve as a contract between the developers of the knowledge graph and its users regarding the meaning of the data. A user could be another human being or a software application needing to interpret the data in a reliable and precise way. of the data and its meanings. When formal semantics are used to express and interpret the data of kuwait whatsapp number data a knowledge graph, there are several representation and modeling instruments:
Classes: Most often, an entity description contains a classification of the entity concerning a class hierarchy. For instance, when dealing with general news or business information, there could be classes that include Person, Organization, and Location. Persons and organizations can have a common super-class agent. Location usually has numerous sub-classes, e.g., Country, Populated place, City, etc.
Relationships: The relationships between entities are usually tagged with types, which provide information about the nature of the relationship, e.g., friend, relative, competitor, etc.
Categories: An entity can be associated with categories that describe some aspect of its semantics, e.g., “Big Four consultants” or “XIX century composers.” A book can belong simultaneously to all these categories: “Books about Africa,” “Bestseller,” “Books by Italian authors,” “Books for kids,” etc. Often categories are described and ordered into a taxonomy.
Free Text: It is possible to add “human-friendly text” to further clarify design intentions for the entity and improve search.