What is a TnT tagger in nltk

This recipe explains what is a TnT tagger in nltk

Recipe Objective

This recipe explains what is a TnT tagger.

Step 1: Importing library

Let us first import the necessary libraries. We'll import treebank and tnt from nltk.corpus and nltk.tag respectively.

from nltk.tag import tnt
from nltk.corpus import treebank

Step 2: TnT Tagger

TnT is a very efficient pos tagger that works on second-order Markov models it can be trained in different languages and on any tagset. The component trains on tagged corpora for parameter generation. For smoothening we use linear insertion. It works best when trained over sentence delimited input. It is still efficient if we separate the training and testing data on all punctuation.

train = treebank.tagged_sents()[:1000]
test = treebank.tagged_sents()[1000:]
tagg = tnt.TnT()
tagg.train(train)
print ("Accuracy of TnT Tagging : ", tagg.evaluate(test))

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