StanfordTokenizer will be deprecated in version 3.2.5 Warning I was testing the StanfordNERTagger using the NLTK wrapper and this warning appeared:

DeprecationWarning: The StanfordTokenizer will be deprecated in version 
3.2.5. Please use nltk.tag.corenlp.CoreNLPPOSTagger or 
nltk.tag.corenlp.CoreNLPNERTagger instead.
super(StanfordNERTagger, self).__init__(*args, **kwargs)


My code looks like this:

from nltk import word_tokenize, pos_tag, ne_chunk
from nltk.tag import StanfordNERTagger

sentence = "Today George went to school and met his friend Peter."

# stanford's NER tagger 3 entity classification
st = StanfordNERTagger('/home/hercules/Desktop/PhD/Tools/stanford-ner-
     2017-06-09/classifiers/english.all.3class.distsim.crf.ser.gz',
     '/home/hercules/Desktop/PhD/Tools/stanford-ner-2017-06-09/stanford-
     ner.jar',
     encoding='utf-8')

tokenized_text = word_tokenize(sentence)
classified_text = st.tag(tokenized_text)

print("Stanford NER tagger:")
print(classified_text)


I tried to use CoreNLPNERTagger but I could not find any examples or documentation. 
I only found this link:
where it gives something like an example in the comments of the 
class CoreNLPNERTagger(CoreNLPTagger)                                      (I found it by searching the keyword "CoreNLPNERTagge")

I tried to follow that example with no use.
I think I should start (if that is the correct term) the coreNLP server first but if is that the case I don't know how.

If anyone got any idea or advice I would be grateful.
@imoutidi, I also encountered the same deprecation warning.

After digging around a bit, it looks like the new/replacement package can be imported with the following:

from nltk.tag.stanford import CoreNLPNERTagger

However, when trying to run the tag() method I end up getting an unexpected HTTP connection refused error. I haven't figured out if this is an environment configuration issue (missing .jar path) or an issue with the NLTK codebase. I tried temporarily turning off my local firewall and that didn't help, so I'm guessing it is one of the other two possibilities.

I hope the python import statement is at least some help.