问题
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.
来源：https://stackoverflow.com/questions/60961208/stanfordcorenlp-server-listening-indefinitely-using-stanza