I have a text dataset. Those dataset consist of many lines that each lines are consist of two sentences split by tab, like this :
this is string 1, first sentence. this is string 2, first sentence.
this is string 1, second sentence. this is string 2, second sentence.
and then I have split the datatext by this code :
#file readdata.py
from globalvariable import *
import os
class readdata:
def dataAyat(self):
global kalimatayat
fo = open(os.path.join('E:\dataset','dataset.txt'),"r")
line = []
for line in fo.readlines():
datatxt = line.rstrip('\n').split('\t')
newdatatxt = [x.split('\t') for x in datatxt]
kalimatayat.append(newdatatxt)
print newdatatxt
readdata().dataAyat()
it works and the output is :
[['this is string 1, first sentence.'],['this is string 2, first sentence.']]
[['this is string 1, second sentence.'],['this is string 2, second sentence.']]
what I want to do is tokenize those list using nltk word tokenize, and the output I expect is like this :
[['this' , 'is' , 'string' , '1' , ',' , 'first' , 'sentence' , '.'],['this' , 'is' , 'string' , '2' , ',' , 'first' , 'sentence' , '.']]
[['this' , 'is' , 'string' , '1' , ',' , 'second' , 'sentence' , '.'],['this' , 'is' , 'string' , '2' , ',' , 'second' , 'sentence' , '.']]
anybody knows how to tokenize to be like the output above? I want to code a tokenize function in "tokenizer.py" and call it all in "mainfile.py"
To tokenize the list of sentences, iterate over it and store the results in a list:
data = [[['this is string 1, first sentence.'],['this is string 2, first sentence.']],
[['this is string 1, second sentence.'],['this is string 2, second sentence.']]]
results = []
for sentence in data:
sentence_results = []
for s in sentence:
sentence_results.append(nltk.word_tokenize(sentence))
results.append(sentence_results)
results will be something like
[[['this' , 'is' , 'string' , '1' , ',' , 'first' , 'sentence' , '.'],
['this' , 'is' , 'string' , '2' , ',' , 'first' , 'sentence' , '.']],
[['this' , 'is' , 'string' , '1' , ',' , 'second' , 'sentence' , '.'],
['this' , 'is' , 'string' , '2' , ',' , 'second' , 'sentence' , '.']]]