There are so many guides on how to tokenize a sentence, but i didn\'t find any on how to do the opposite.
import nltk
words = nltk.word_tokenize(\"I\'ve found
I am using following code without any major library function for detokeization purpose. I am using detokenization for some specific tokens
_SPLITTER_ = r"([-.,/:!?\";)(])"
def basic_detokenizer(sentence):
""" This is the basic detokenizer helps us to resolves the issues we created by our tokenizer"""
detokenize_sentence =[]
words = sentence.split(' ')
pos = 0
while( pos < len(words)):
if words[pos] in '-/.' and pos > 0 and pos < len(words) - 1:
left = detokenize_sentence.pop()
detokenize_sentence.append(left +''.join(words[pos:pos + 2]))
pos +=1
elif words[pos] in '[(' and pos < len(words) - 1:
detokenize_sentence.append(''.join(words[pos:pos + 2]))
pos +=1
elif words[pos] in ']).,:!?;' and pos > 0:
left = detokenize_sentence.pop()
detokenize_sentence.append(left + ''.join(words[pos:pos + 1]))
else:
detokenize_sentence.append(words[pos])
pos +=1
return ' '.join(detokenize_sentence)