Sentence tokenization for texts that contains quot

Code:

from nltk.tokenize import sent_tokenize           
pprint(sent_tokenize(unidecode(text)))

Output:

[After Du died of suffocation, her boyfriend posted a heartbreaking message online: "Losing consciousness in my arms, your breath and heartbeat became weaker and weaker.',
 'Finally they pushed you out of the cold emergency room.',
 'I failed to protect you.',
 '"Li Na, 23, a migrant worker from a farming family in Jiangxi province, was looking forward to getting married in 2015.',]

Input:

After Du died of suffocation, her boyfriend posted a heartbreaking message online: "Losing consciousness in my arms, your breath and heartbeat became weaker and weaker. Finally they pushed you out of the cold emergency room. I failed to protect you."

Li Na, 23, a migrant worker from a farming family in Jiangxi province, was looking forward to getting married in 2015.

Quotes should be included in previous sentence. Instead of " Li.

It fails at ." How to fix this?

Edit: Explaining the extraction of text.

html = open(path, "r").read()                           #reads html code
article = extractor.extract(raw_html=html)              #extracts content
text = unidecode(article.cleaned_text)                  #changes encoding

Here, article.cleaned_text is in unicode. The idea behind using this to change characters “ to ".

Solutions @alvas Incorrect Result:

['After Du died of suffocation, her boyfriend posted a heartbreaking message online: "Losing consciousness in my arms, your breath and heartbeat became weaker and weaker.',
 'Finally they pushed you out of the cold emergency room.',
 'I failed to protect you.',
 '"',
 'Li Na, 23, a migrant worker from a farming family in Jiangxi province, was looking forward to getting married in 2015.'
]

Edit2: (Updated) nltk and python version

python -c "import nltk; print nltk.__version__"
3.0.4
python -V
Python 2.7.9

I'm not sure what is the desired output but I think you might need some paragraph segmentation before nltk.sent_tokenize, i.e.:

>>> text = """After Du died of suffocation, her boyfriend posted a heartbreaking message online: "Losing consciousness in my arms, your breath and heartbeat became weaker and weaker. Finally they pushed you out of the cold emergency room. I failed to protect you."
... 
... Li Na, 23, a migrant worker from a farming family in Jiangxi province, was looking forward to getting married in 2015."""
>>> from nltk import sent_tokenize
>>> paragraphs = text.split('\n\n')
>>> for pg in paragraphs:
...     for sent in sent_tokenize(pg):
...             print sent
... 
After Du died of suffocation, her boyfriend posted a heartbreaking message online: "Losing consciousness in my arms, your breath and heartbeat became weaker and weaker.
Finally they pushed you out of the cold emergency room.
I failed to protect you."
Li Na, 23, a migrant worker from a farming family in Jiangxi province, was looking forward to getting married in 2015.

Possibly, you might want strings within the double quotes too, if so you could try this:

>>> import re
>>> str_in_doublequotes = r'"([^"]*)"'
>>> re.findall(str_in_doublequotes, text)
['Losing consciousness in my arms, your breath and heartbeat became weaker and weaker. Finally they pushed you out of the cold emergency room. I failed to protect you.']

Or maybe you would need this:

>>> for pg in paragraphs:
...     # Collects the quotes inside the paragraph 
...     in_quotes = re.findall(str_in_doublequotes, pg)
...     for q in in_quotes:
...             # Keep track of the quotes with tabs.
...             pg = pg.replace('"{}"'.format(q), '\t')
...     for _pg in pg.split('\t'):
...             for sent in sent_tokenize(_pg):
...                     print sent
...             try:
...                     print '"{}"'.format(in_quotes.pop(0))
...             except IndexError: # Nothing to pop.
...                     pass
... 
After Du died of suffocation, her boyfriend posted a heartbreaking message online: 
"Losing consciousness in my arms, your breath and heartbeat became weaker and weaker. Finally they pushed you out of the cold emergency room. I failed to protect you."
Li Na, 23, a migrant worker from a farming family in Jiangxi province, was looking forward to getting married in 2015.

When reading from file, try to use the io package:

alvas@ubi:~$ echo -e """After Du died of suffocation, her boyfriend posted a heartbreaking message online: \"Losing consciousness in my arms, your breath and heartbeat became weaker and weaker. Finally they pushed you out of the cold emergency room. I failed to protect you.\"\n\nLi Na, 23, a migrant worker from a farming family in Jiangxi province, was looking forward to getting married in 2015.""" > in.txt
alvas@ubi:~$ cat in.txt 
After Du died of suffocation, her boyfriend posted a heartbreaking message online: "Losing consciousness in my arms, your breath and heartbeat became weaker and weaker. Finally they pushed you out of the cold emergency room. I failed to protect you."

Li Na, 23, a migrant worker from a farming family in Jiangxi province, was looking forward to getting married in 2015.
alvas@ubi:~$ python
Python 2.7.6 (default, Jun 22 2015, 17:58:13) 
[GCC 4.8.2] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import io
>>> from nltk import sent_tokenize
>>> text = io.open('in.txt', 'r', encoding='utf8').read()
>>> print text
After Du died of suffocation, her boyfriend posted a heartbreaking message online: "Losing consciousness in my arms, your breath and heartbeat became weaker and weaker. Finally they pushed you out of the cold emergency room. I failed to protect you."

Li Na, 23, a migrant worker from a farming family in Jiangxi province, was looking forward to getting married in 2015.

>>> for sent in sent_tokenize(text):
...     print sent
... 
After Du died of suffocation, her boyfriend posted a heartbreaking message online: "Losing consciousness in my arms, your breath and heartbeat became weaker and weaker.
Finally they pushed you out of the cold emergency room.
I failed to protect you."
Li Na, 23, a migrant worker from a farming family in Jiangxi province, was looking forward to getting married in 2015.

And with the paragraph and quote extraction hacks:

>>> import io, re
>>> from nltk import sent_tokenize
>>> str_in_doublequotes = r'"([^"]*)"'
>>> paragraphs = text.split('\n\n')
>>> for pg in paragraphs:
...     # Collects the quotes inside the paragraph 
...     in_quotes = re.findall(str_in_doublequotes, pg)
...     for q in in_quotes:
...             # Keep track of the quotes with tabs.
...             pg = pg.replace('"{}"'.format(q), '\t')
...     for _pg in pg.split('\t'):
...             for sent in sent_tokenize(_pg):
...                     print sent
...             try:
...                     print '"{}"'.format(in_quotes.pop(0))
...             except IndexError: # Nothing to pop.
...                     pass
... 
After Du died of suffocation, her boyfriend posted a heartbreaking message online: 
"Losing consciousness in my arms, your breath and heartbeat became weaker and weaker. Finally they pushed you out of the cold emergency room. I failed to protect you."
Li Na, 23, a migrant worker from a farming family in Jiangxi province, was looking forward to getting married in 2015.

For the magic to concatenate the pre-quote sentence with the quotes (don't blink, it looks quite the same as above):

>>> import io, re
>>> from nltk import sent_tokenize
>>> str_in_doublequotes = r'"([^"]*)"'
>>> paragraphs = text.split('\n\n')
>>> for pg in paragraphs:
...     # Collects the quotes inside the paragraph 
...     in_quotes = re.findall(str_in_doublequotes, pg)
...     for q in in_quotes:
...             # Keep track of the quotes with tabs.
...             pg = pg.replace('"{}"'.format(q), '\t')
...     for _pg in pg.split('\t'):
...             for sent in sent_tokenize(_pg):
...                     print sent,
...             try:
...                     print '"{}"'.format(in_quotes.pop(0))
...             except IndexError: # Nothing to pop.
...                     pass
... 
After Du died of suffocation, her boyfriend posted a heartbreaking message online:  "Losing consciousness in my arms, your breath and heartbeat became weaker and weaker. Finally they pushed you out of the cold emergency room. I failed to protect you."
Li Na, 23, a migrant worker from a farming family in Jiangxi province, was looking forward to getting married in 2015.

The problem with the above code is that it is limited to sentences like:

After Du died of suffocation, her boyfriend posted a heartbreaking message online: "Losing consciousness in my arms, your breath and heartbeat became weaker and weaker. Finally they pushed you out of the cold emergency room. I failed to protect you."

And cannot handle:

"Losing consciousness in my arms, your breath and heartbeat became weaker and weaker. Finally they pushed you out of the cold emergency room. I failed to protect you," her boyfriend posted a heartbreaking message online after Du died of suffocation.

Just to make sure, my python/nltk versions are:

$ python -c "import nltk; print nltk.__version__"
'3.0.3'
$ python -V
Python 2.7.6

Beyond the computational aspect of the text processing, there's something subtly different about the grammar of the text in the question.

The fact that a quote is followed by a semi-colon : is untypical of the traditional English grammar. This might have been popularized in the Chinese news because in Chinese: