Python Untokenize a sentence

Question

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          


        

Answer 1

I propose to keep offsets in tokenization: (token, offset). I think, this information is useful for processing over the original sentence.

import re
from nltk.tokenize import word_tokenize

def offset_tokenize(text):
    tail = text
    accum = 0
    tokens = self.tokenize(text)
    info_tokens = []
    for tok in tokens:
        scaped_tok = re.escape(tok)
        m = re.search(scaped_tok, tail)
        start, end = m.span()
        # global offsets
        gs = accum + start
        ge = accum + end
        accum += end
        # keep searching in the rest
        tail = tail[end:]
        info_tokens.append((tok, (gs, ge)))
    return info_token

sent = '''I've found a medicine for my disease.

This is line:3.'''

toks_offsets = offset_tokenize(sent)

for t in toks_offsets:
(tok, offset) = t
print (tok == sent[offset[0]:offset[1]]), tok, sent[offset[0]:offset[1]]

Gives:

True I I
True 've 've
True found found
True a a
True medicine medicine
True for for
True my my
True disease disease
True . .
True This This
True is is
True line:3 line:3
True . .

Answer 2

You can use "treebank detokenizer" - TreebankWordDetokenizer:

from nltk.tokenize.treebank import TreebankWordDetokenizer
TreebankWordDetokenizer().detokenize(['the', 'quick', 'brown'])
# 'The quick brown'

---

There is also MosesDetokenizer which was in nltk but got removed because of the licensing issues, but it is available as a Sacremoses standalone package.

Answer 3

The reason tokenize.untokenize does not work is because it needs more information than just the words. Here is an example program using tokenize.untokenize:

from StringIO import StringIO
import tokenize

sentence = "I've found a medicine for my disease.\n"
tokens = tokenize.generate_tokens(StringIO(sentence).readline)
print tokenize.untokenize(tokens)

Additional Help: Tokenize - Python Docs | Potential Problem

Answer 4

use token_utils.untokenize from here

import re
def untokenize(words):
    """
    Untokenizing a text undoes the tokenizing operation, restoring
    punctuation and spaces to the places that people expect them to be.
    Ideally, `untokenize(tokenize(text))` should be identical to `text`,
    except for line breaks.
    """
    text = ' '.join(words)
    step1 = text.replace("`` ", '"').replace(" ''", '"').replace('. . .',  '...')
    step2 = step1.replace(" ( ", " (").replace(" ) ", ") ")
    step3 = re.sub(r' ([.,:;?!%]+)([ \'"`])', r"\1\2", step2)
    step4 = re.sub(r' ([.,:;?!%]+)$', r"\1", step3)
    step5 = step4.replace(" '", "'").replace(" n't", "n't").replace(
         "can not", "cannot")
    step6 = step5.replace(" ` ", " '")
    return step6.strip()

 tokenized = ['I', "'ve", 'found', 'a', 'medicine', 'for', 'my','disease', '.']
 untokenize(tokenized)
 "I've found a medicine for my disease."