A system to determine all likely part of speech (POS) tagging using the Viterbi algorithm to judge ambiguity of the input, uncertainty of the tagger and the need to backtrack to the next most probable tagging. Implemented normalization, Laplace Smoothing and Hidden Markov Model using Prolog, Bash and NLTK.
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A system to determine all likely part of speech (POS) tagging using the Viterbi algorithm to judge ambiguity of the input, uncertainty of the tagger and the need to backtrack to the next most probable tagging. Implemented normalization, Laplace Smoothing and Hidden Markov Model using Prolog, Python, Bash and NLTK.
SysJunkie/PartOfSpeechTaggerToJudgeAmbiguity
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A system to determine all likely part of speech (POS) tagging using the Viterbi algorithm to judge ambiguity of the input, uncertainty of the tagger and the need to backtrack to the next most probable tagging. Implemented normalization, Laplace Smoothing and Hidden Markov Model using Prolog, Python, Bash and NLTK.
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