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Conditional Random Field (CRF) is a statistical modeling method often used for structured prediction. It's a type of discriminative undirected probabilistic graphical model that predicts a sequence of labels for a sequence of input samples. It's particularly used in tasks like named entity recognition, part of speech tagging, and text chunking where context is crucial to predict the output. Unlike other methods, CRF takes into account the context within the input sequence to make a prediction, which often results in improved accuracy.

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