corenlp.py CoreNLPServer throws TypeError exception

Hello,

Here’s the code:

>>> s = nltk.parse.corenlp.CoreNLPServer(path_to_jar='/usr/local/share/stanford/stanford-corenlp-3.8.0.jar', path_to_models_jar='/usr/local/share/stanford/stanford-english-corenlp-2017-06-09-models.jar')
Traceback (most recent call last):
  File "<input>", line 1, in <module>
    s = nltk.parse.corenlp.CoreNLPServer(path_to_jar='/usr/local/share/stanford/stanford-corenlp-3.8.0.jar', path_to_models_jar='/usr/local/share/stanford/stanford-english-corenlp-2017-06-09-models.jar')
  File "/Users/adiep/feedback-sentiment/.env/src/nltk/nltk/parse/corenlp.py", line 69, in __init__
    key=lambda model_name: re.match(self._JAR, model_name)
TypeError: '>' not supported between instances of 'NoneType' and 'NoneType'

The max function is throwing this exception.

I think what’s happening is that key=lambda model_name: re.match(self._JAR, model_name) is returning NoneType because it didn’t match anything. So it fills the list of NoneType and max fails to sort it. I found that self._JAR and model_name evaluated to the following:

>>> type(re.match(r'stanford-corenlp-(\d+)\.(\d+)\.(\d+)\.jar', '/usr/local/share/stanford/stanford-corenlp-3.8.0.jar'))
<class 'NoneType'>

Thanks,

[f0lie]

Good lord, now it’s working.

So overall, I had to change re.match to re.search.group and kill a floating corenlpserver in the background.

Maybe there should be some code to detect if there is other corenlpservers running? Don’t know if it’s even worth doing.

[dimazest]

Hi, I’m sorry that there is no documentation. The API has changed, here are is what you need to do. Refer to #1510, it contains a long discussion on how to start a server.

The main change: NLTK does not start CoreNLP server, you need to start it. Refer to https://stanfordnlp.github.io/CoreNLP/corenlp-server.html for a detailed explanation, but the command should be something like:

# Run the server using all jars in the current directory (e.g., the CoreNLP home directory)
java -mx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer -port 9000 -timeout 15000

Open http://localhost:9000/ to make sure that the server is running.

Now you are ready to use NLTK corenlp client:

tagger = CoreNLPNERTagger(url='http://localhost:9000')
tokens = tagger.tag(text)

Please let me know if it works.