Exercises a tagger on a large corpus might take a large opportunity. As a substitute to training a tagger every time we want one, it’s easy to cut a tuned tagger in a file for eventually re-use. Let us save our very own tagger t2 to a file t2.pkl .
At this point, in a different Python procedure, we are going to load our stored tagger.
Right now why don’t we make certain it can be used for labeling.
What’s the maximum toward the overall performance of an n-gram tagger? Think about the case of a trigram tagger. What number of cases of part-of-speech ambiguity will it discover? We could establish the answer to this issue empirically: