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In principle, natural language and knowledge representation are closely related. This paper investigates this by demonstrating how several natural language phenomena, such as definite reference, ambiguity, ellipsis, ill-formed input, figures of speech, and vagueness, require diverse knowledge sources and reasoning. The breadth of kinds of knowledge needed to represent morphology, syntax, semantics, and pragmatics is surveyed. Furthermore, several current issues in knowledge representation, such as logic versus semantic nets, general-purpose versus special-purpose reasoners, adequacy of first-order logic, wait-and-see strategies, and default reasoning, are illustrated in terms of their relation to natural language processing and how natural language impacts the issues. We conclude that a significant breakthrough in either natural language processing or in knowledge representation could lead to a breakthrough in the other.