In Artificial Intelligence , a semantic network

Answer: is a graph-based method of knowledge representation where nodes represent concepts and arcs represent relations between concepts.

Explanation: A semantic network models knowledge as a graph. Its key elements are:

• Nodes: represent concepts, objects, events, or propositions.

• Arcs (edges): represent labeled relationships between nodes, such as "is-a", "part-of", or other semantic relations.

Why the correct statement is right:

• The graph structure directly encodes conceptual relationships, making inheritance and associative queries straightforward.

• It is primarily a representational formalism, not a logical language; translations to logical expressions are possible but not required.

Common confusions (brief):

• Describing entities as slots refers to frame/slot representations, not semantic networks.

• Saying that arcs are concepts and nodes are relations reverses the actual roles in the graph.

• Semantic networks are not inherently a subset of first-order logic; they are a different representational approach that can sometimes be mapped to logical formulas.

Simple example: cat — is-a → mammal; mammal — is-a → animal