I am trying to calculate the time required to tag one sentence/file by one
trained NLTK HMM Tagger.
To do this I am writing the following code, please suggest if I need to revise
anything here.
import nltk
from nltk.corpus.reader import TaggedCorpusReader
import time
#HMM
reader = TaggedCorpusReader('/python27/', r'.*\.pos')
f1=reader.fileids()
print f1
sents=reader.tagged_sents()
ls=len(sents)
print "Total No of Sentences:",ls
train_sents=sents[0:40]
test_sents=sents[41:46]
#TRAINING & TESTING
hmm_tagger=nltk.HiddenMarkovModelTagger.train(train_sents)
test=hmm_tagger.test(test_sents)
appli_sent1=reader.sents(fileids='minicv.pos')[0]
print "SAMPLE INPUT:",appli_sent1
#TIME CALCULATION
start_time = time.clock()
application=hmm_tagger.tag(appli_sent1) #I MAY REPLACE WITH ONE DOCUMENT
print "ENTITY RECOGNIZED",application
print "Time Taken Is:",time.clock() - start_time, "seconds"
NB: This is a toy kind example and I did not follow much of training/testing
size parameters.
My question is only for the time calculation part. It is not a forum for
Machine Learning, but as there are many people who has very high level
knowledge on it, any one is most welcome to give his/her valuable feedback
which may improve my knowledge.
As the code is pasted here from IDLE (with Python2.7 on MS-Windows 7) I could
not maintain proper indentation, apology for the same.
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