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Load a labeled data set (see README.txt for data formatting details) and experiment with various labeling interfaces for training a model against a benchmark corpus. If a test set is supplied, it must be labeled, and the training set may be unlabeled. If only a training set is supplied, it must be labeled and a train (90%) / test (10%) split will be created automatically.
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