The most simple networks, which are used in artificial intelligence systems - relational graphs of quadratic equations. They consist of nodes connected by arcs. Each node represents a concept, and each arc - the relationship between different concepts. Figure 1 presents the sentence "The dog eagerly glozhet bone. Four rectangles represent the notion of a dog, a process glozheniya, bones, and such characteristics as greed. Inscriptions on the arcs indicate that the dog is the agent glozheniya, bone is the object of glozheniya and greed - this way glozheniya.
The terminology used in this area varies. To achieve some uniformity, nodes connected by arcs, commonly called a graphs of quadratic equations, a structure where there is a whole nest of the nodes, or where there are relationships between the different order of columns is called a network. In addition to the terminology used to explain, as different methods of image. Some use mugs instead of rectangles, some types of writing directly on the arcs, not enclosing them in ovals, and some use abbreviations, such as O or A to denote the agent or object, and some use different types of arrows. Figure 2 shows a graphs of quadratic equations of the conceptual dependency Shenk. <=> Means the agent. INGEST (absorb) - one of the primitives Shenk: YES - to absorb a solid object; drink - the object to absorb liquid; Breathing - absorb gaseous object. Additional windows on the left shows that the transition from bone to the dog an unspecified location.
Since it is difficult to put into the computer, some charts and they occupy much space in the press, many scholars write their entry in the more compact form. For example, the same sentence Owl invited to write in a linear form, using some elements of Figure 1
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