I am trying to run the java Stanford CoreNLP package using a python wrapper called Stanza. I am simply trying to run the example provided on the website. I am not using any virtual environment. Here is the example I am running.
Whenever I run the java server, it just hangs at listening or eventually times out. I followed the instruction provided with the example and set the CORENLP_HOME variable. I was initially running the code through PyCharm but then I also observed the same behavior when I run it through the terminal.
I have been observing the same behavior if I try running the java server directly from the terminal rather than using a wrapper (which I have to) and also when I used another python wrapper called stanford-corenlp. I did download the full model from the website.
Samarths-MacBook-Pro-2:analysis samarthbhandari$ python stanza_test.py
---
input text
Chris Manning is a nice person. Chris wrote a simple sentence. He also gives oranges to people.
---
starting up Java Stanford CoreNLP Server...
Starting server with command: java -Xmx16G -cp /path/to/stanford-corenlp-full-2018-10-05/* edu.stanford.nlp.pipeline.StanfordCoreNLPServer -port 9000 -timeout 1000 -threads 5 -maxCharLength 100000 -quiet False -serverProperties corenlp_server-3694fc014d83421c.props -preload tokenize,ssplit,pos,lemma,ner,parse,depparse,coref
[main] INFO CoreNLP - --- StanfordCoreNLPServer#main() called ---
[main] INFO CoreNLP - setting default constituency parser
[main] INFO CoreNLP - warning: cannot find edu/stanford/nlp/models/srparser/englishSR.ser.gz
[main] INFO CoreNLP - using: edu/stanford/nlp/models/lexparser/englishPCFG.ser.gz instead
[main] INFO CoreNLP - to use shift reduce parser download English models jar from:
[main] INFO CoreNLP - http://stanfordnlp.github.io/CoreNLP/download.html
[main] INFO CoreNLP - Threads: 5
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator tokenize
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator ssplit
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator pos
[main] INFO edu.stanford.nlp.tagger.maxent.MaxentTagger - Loading POS tagger from edu/stanford/nlp/models/pos-tagger/english-left3words/english-left3words-distsim.tagger ... done [0.4 sec].
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator lemma
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator ner
[main] INFO edu.stanford.nlp.ie.AbstractSequenceClassifier - Loading classifier from edu/stanford/nlp/models/ner/english.all.3class.distsim.crf.ser.gz ... done [1.5 sec].
[main] INFO edu.stanford.nlp.ie.AbstractSequenceClassifier - Loading classifier from edu/stanford/nlp/models/ner/english.muc.7class.distsim.crf.ser.gz ... done [1.0 sec].
[main] INFO edu.stanford.nlp.ie.AbstractSequenceClassifier - Loading classifier from edu/stanford/nlp/models/ner/english.conll.4class.distsim.crf.ser.gz ... done [0.5 sec].
[main] INFO edu.stanford.nlp.time.JollyDayHolidays - Initializing JollyDayHoliday for SUTime from classpath edu/stanford/nlp/models/sutime/jollyday/Holidays_sutime.xml as sutime.binder.1.
[main] INFO edu.stanford.nlp.time.TimeExpressionExtractorImpl - Using following SUTime rules: edu/stanford/nlp/models/sutime/defs.sutime.txt,edu/stanford/nlp/models/sutime/english.sutime.txt,edu/stanford/nlp/models/sutime/english.holidays.sutime.txt
[main] INFO edu.stanford.nlp.pipeline.TokensRegexNERAnnotator - ner.fine.regexner: Read 580704 unique entries out of 581863 from edu/stanford/nlp/models/kbp/english/gazetteers/regexner_caseless.tab, 0 TokensRegex patterns.
[main] INFO edu.stanford.nlp.pipeline.TokensRegexNERAnnotator - ner.fine.regexner: Read 4869 unique entries out of 4869 from edu/stanford/nlp/models/kbp/english/gazetteers/regexner_cased.tab, 0 TokensRegex patterns.
[main] INFO edu.stanford.nlp.pipeline.TokensRegexNERAnnotator - ner.fine.regexner: Read 585573 unique entries from 2 files
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator parse
[main] INFO edu.stanford.nlp.parser.common.ParserGrammar - Loading parser from serialized file edu/stanford/nlp/models/lexparser/englishPCFG.ser.gz ... done [0.2 sec].
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator depparse
[main] INFO edu.stanford.nlp.parser.nndep.DependencyParser - Loading depparse model: edu/stanford/nlp/models/parser/nndep/english_UD.gz ...
[main] INFO edu.stanford.nlp.parser.nndep.Classifier - PreComputed 99996, Elapsed Time: 7.781 (s)
[main] INFO edu.stanford.nlp.parser.nndep.DependencyParser - Initializing dependency parser ... done [12.9 sec].
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator coref
[main] INFO edu.stanford.nlp.coref.statistical.SimpleLinearClassifier - Loading coref model edu/stanford/nlp/models/coref/statistical/ranking_model.ser.gz ... done [0.6 sec].
[main] INFO edu.stanford.nlp.pipeline.CorefMentionAnnotator - Using mention detector type: dependency
[main] INFO CoreNLP - Starting server...
[main] INFO CoreNLP - StanfordCoreNLPServer listening at /0:0:0:0:0:0:0:0:9000
As you can see from the output (using the be_quiet=False verbose mode) it just keeps listening and does not proceed to processing anything, or printing anything that is mentioned in the example linked above. Eventually it just times out.