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Categorical alignment refers to the process of ensuring that different categories or classifications within a dataset or model align appropriately with each other, promoting consistency and clarity. This concept is often applied in contexts such as data analysis, machine learning, and natural language processing, where accurate categorization is crucial for effective outcomes. Proper categorical alignment helps in avoiding biases and misinterpretations by establishing a clear framework for how categories relate to one another.

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