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5.  def buildTagBook(taggedSentences: Array[TaggedSentence], frequencyThreshold: Int, ambiguityThreshold: Double): Map[String, String]

   Finds very frequent tags on a word in training, and marks them as non ambiguous based on tune parameters ToDo: Move such parameters to configuration

   Finds very frequent tags on a word in training, and marks them as non ambiguous based on tune parameters ToDo: Move such parameters to configuration

   taggedSentences

   Takes entire tagged sentences to find frequent tags

   frequencyThreshold

   How many times at least a tag on a word to be marked as frequent

   ambiguityThreshold

   How much percentage of total amount of words are covered to be marked as frequent

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10.  def generatesTagBook(dataset: Dataset[_]): Array[TaggedSentence]

    Generates TagBook, which holds all the word to tags mapping that are not ambiguous

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19.  def trainPerceptron(nIterations: Int, initialModel: TrainingPerceptronLegacy, taggedSentences: Array[TaggedSentence], taggedWordBook: Map[String, String]): AveragedPerceptron

    Iterates for training

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