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I understand that HMM models model language with Parts of Speech (POS) as hidden states and words as observations. These HMM models are usually learned from large text corpora, and many of these corpora are publicly available. Where can I find such models with their parameters, i.e., the list of POS or other hidden states, observed words, the transition probabilities, and emission probabilities. I don't care whether the models is learned statistically from a large corpus or from expert knowledge or some combination. I need trained models that I can use. Are there any public sources for such knowledge?

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Python NLTK has a dataset called hmm_treebank_pos_tagger that you can download here. Stanford has a POS tagger described here. You can download it along with the training data

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http://wordnet.princeton.edu/ not directly what you are after, but might be useful. It has a large list of words, stems and many different linkages between them. It was useful to me as a resource creating an NLP engine

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