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The Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text. It supports the most common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, and coreference resolution.


F# extensions for Stanford.NLP.NET that provide: Strongly-typed set of Penn Treebank II tags; Active patterns for tags classification; Helper functions for java.util.Iterable.


MaltParser is a system for data-driven dependency parsing, which can be used to induce a parsing model from treebank data and to parse new data using an induced mode


F# Type Provider for Stanford NLP TokensRegex (generic framework included in Stanford CoreNLP for defining patterns over text (sequences of tokens) and mapping it to semantic objects represented as Java objects).