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For Natural Process Language: Problem 4: Brill Tagging. (a) Consider the following sentence and two different taggings: Most likely tags: John/NNP made/VBD up/IN the/DT story/NN.I.

For Natural Process Language:image text in transcribed

Problem 4: Brill Tagging. (a) Consider the following sentence and two different taggings: Most likely tags: John/NNP made/VBD up/IN the/DT story/NN.I. Correct tags: John/NNP made/VBD up/RP the/DT story/NN... Instantiate each of Brill's templates for the "before" or preceding" cases (Figure 5.20 in the book) given this data to generate 6 transformations (that is, do not instantiate templates using "following" or "after"). (b) Considering examples 5.4-5.6 in the book, which of these transformations do you think will be most effective on a large corpus, and why? /NNP Shaefer/NNP never/RB got/VBD around/RP to/TO joining/VBG All/DT we/PRP gotta/VBN do/VB is/VBZ go/VB around/IN the/DT corner/NN Chateau/NNP Petrus/NNP costs/VBZ around/RB 250/CD Problem 4: Brill Tagging. (a) Consider the following sentence and two different taggings: Most likely tags: John/NNP made/VBD up/IN the/DT story/NN.I. Correct tags: John/NNP made/VBD up/RP the/DT story/NN... Instantiate each of Brill's templates for the "before" or preceding" cases (Figure 5.20 in the book) given this data to generate 6 transformations (that is, do not instantiate templates using "following" or "after"). (b) Considering examples 5.4-5.6 in the book, which of these transformations do you think will be most effective on a large corpus, and why? /NNP Shaefer/NNP never/RB got/VBD around/RP to/TO joining/VBG All/DT we/PRP gotta/VBN do/VB is/VBZ go/VB around/IN the/DT corner/NN Chateau/NNP Petrus/NNP costs/VBZ around/RB 250/CD

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