In artificial intelligence terminology, what type of repository does AI primarily operate on, in contrast to conventional data-processing systems that focus on raw records and transactions?

Introduction / Context:
Artificial intelligence systems aim to mimic aspects of human reasoning by using structured representations of facts, rules, and relationships. Instead of merely storing rows and columns of data, AI leverages formal knowledge to infer new conclusions, answer queries, and explain decisions.

Given Data / Assumptions:

• We contrast traditional databases with AI-oriented repositories.
• AI systems may use production rules, ontologies, or semantic networks.
• We are identifying the term that best captures this repository.

Concept / Approach:
A knowledge base stores assertions (facts) and inference rules in a form the reasoning engine (inference engine) can use. Databases, while sometimes enriched with constraints and triggers, are not primarily designed for inference over symbolic knowledge. Languages such as PROLOG and LISP are tools; they are not the repositories themselves. Therefore, the correct choice is 'knowledge base.'

Step-by-Step Solution:

Verification / Alternative check:
Expert systems and knowledge graphs exemplify knowledge bases driving inference and question answering.

Why Other Options Are Wrong:

Common Pitfalls:
Confusing storage mechanisms with reasoning engines; assuming any data store equals knowledge.

Final Answer:
Knowledge base