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Rule-Based Tagging
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- given input sentence we assign each word ALL POSSIBLE PoS tags, according to dictionary
- then we use rules to REMOVE tags, until each word has exactly one PoS Tag
- rules a hand built (not auto-learned)
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Transformation-Based PoS Tagging
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- given input sentence we assign each word a SINGLE PoS tag, according to dictionary
- then we use rules to TRANSFORM tags, until no more transformations are made
- rules can be auto-learned by feeding it training corpus
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Statistical-Based Tagging
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- given input sentence we assign a PoS Tag to each word that maximizes the probability of being “correct”
- probabilities can be auto-learned by feeding it training corpus
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