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Stanford CoreNLP provides a set of natural language analysis tools which can take raw English language text input and give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, times, and numeric quantities, mark up the structure of sentences in terms of phrases and word dependencies, and indicate which noun phrases refer to the same entities. It provides the foundational building blocks for higher level text understanding applications.

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/**
 * A package for doing inference with conditional random fields.  This
 * implements the common, standard case of a linear chain CRF of arbitrary
 * order (though usually first order in practice) where each position can
 * be labeled with one of a fixed set of classes.
 * 
 * Through the use of different
 * edu.stanford.nlp.sequences.FeatureFactory classes and different
 * edu.stanford.nlp.sequences.DocumentReaderAndWriter classes,
 * it can read data in various formats, and be customized for various
 * sequence inference tasks.  Most of its use has been for Named Entity
 * Recognition, but it has also been used for other applications such as
 * Chinese word segmentation and OCR.
 * 
 * For more usage information, consult the Javadoc of the
 * CRFClassifier class.
 * @author Jenny Finkel
 */
package edu.stanford.nlp.ie.crf;