Python 3.x 使用PyNER的Stanford名称实体识别器（NER）不工作

我正在尝试使用斯坦福大学的名称实体识别器（NER）

我从以下位置下载了zip文件：

使用：python setup.py install安装

现在，当我运行下面的命令时，我得到的是空白输出

import ner
tagger =ner.SocketNER(host='localhost',port=31752,output_format='slashTags')
tagger.get_entities("University of California is located in California, United States")

Output:
{}

我遗漏了什么吗？

这个工具已经严重过时了

如果您正在使用NLTK，请首先更新您的

NLTK

版本：

pip3 install -U nltk

然后仍然在终点站：

wget http://nlp.stanford.edu/software/stanford-corenlp-full-2018-02-27.zip
unzip stanford-corenlp-full-2018-02-27.zip
java -mx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer -preload tokenize,ssplit,pos,lemma,ner,parse,depparse -status_port 9000 -port 9000 -timeout 15000 &

然后在Python3中：

>>> from nltk.parse import CoreNLPParser
>>> tagger = CoreNLPParser(url='http://localhost:9000', tagtype='ner')
>>> tokens = 'Rami Eid is studying at Stony Brook University in NY'.split()
>>> 
>>> tagger.tag(tokens)
[('Rami', 'PERSON'), ('Eid', 'PERSON'), ('is', 'O'), ('studying', 'O'), ('at', 'O'), ('Stony', 'ORGANIZATION'), ('Brook', 'ORGANIZATION'), ('University', 'ORGANIZATION'), ('in', 'O'), ('NY', 'STATE_OR_PROVINCE')]

>>> from nltk.parse import CoreNLPParser
>>> tagger = CoreNLPParser(url='http://localhost:9000', tagtype='ner')
>>> tokens = 'Rami Eid is studying at Stony Brook University in NY'.split()
>>> 
>>> tagger.tag(tokens)
[('Rami', 'PERSON'), ('Eid', 'PERSON'), ('is', 'O'), ('studying', 'O'), ('at', 'O'), ('Stony', 'ORGANIZATION'), ('Brook', 'ORGANIZATION'), ('University', 'ORGANIZATION'), ('in', 'O'), ('NY', 'STATE_OR_PROVINCE')]

---

窗户 您可以使用

powershell

（您确实是这样做的）使用上述功能，但如果您喜欢单击鼠标

步骤1:从下载zip文件

第二步：解压

第3步：打开命令提示符并转到文件解压缩的文件夹

步骤4:运行命令：

pip3安装-U nltk

步骤5:现在运行命令：

java -mx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer -preload tokenize,ssplit,pos,lemma,ner,parse,depparse -status_port 9000 -port 9000 -timeout 15000 &

然后在Python3中：

>>> from nltk.parse import CoreNLPParser
>>> tagger = CoreNLPParser(url='http://localhost:9000', tagtype='ner')
>>> tokens = 'Rami Eid is studying at Stony Brook University in NY'.split()
>>> 
>>> tagger.tag(tokens)
[('Rami', 'PERSON'), ('Eid', 'PERSON'), ('is', 'O'), ('studying', 'O'), ('at', 'O'), ('Stony', 'ORGANIZATION'), ('Brook', 'ORGANIZATION'), ('University', 'ORGANIZATION'), ('in', 'O'), ('NY', 'STATE_OR_PROVINCE')]

>>> from nltk.parse import CoreNLPParser
>>> tagger = CoreNLPParser(url='http://localhost:9000', tagtype='ner')
>>> tokens = 'Rami Eid is studying at Stony Brook University in NY'.split()
>>> 
>>> tagger.tag(tokens)
[('Rami', 'PERSON'), ('Eid', 'PERSON'), ('is', 'O'), ('studying', 'O'), ('at', 'O'), ('Stony', 'ORGANIZATION'), ('Brook', 'ORGANIZATION'), ('University', 'ORGANIZATION'), ('in', 'O'), ('NY', 'STATE_OR_PROVINCE')]

这工具已经严重过时了

如果您正在使用NLTK，请首先更新您的

NLTK

版本：

pip3 install -U nltk

然后仍然在终点站：

wget http://nlp.stanford.edu/software/stanford-corenlp-full-2018-02-27.zip
unzip stanford-corenlp-full-2018-02-27.zip
java -mx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer -preload tokenize,ssplit,pos,lemma,ner,parse,depparse -status_port 9000 -port 9000 -timeout 15000 &

然后在Python3中：

>>> from nltk.parse import CoreNLPParser
>>> tagger = CoreNLPParser(url='http://localhost:9000', tagtype='ner')
>>> tokens = 'Rami Eid is studying at Stony Brook University in NY'.split()
>>> 
>>> tagger.tag(tokens)
[('Rami', 'PERSON'), ('Eid', 'PERSON'), ('is', 'O'), ('studying', 'O'), ('at', 'O'), ('Stony', 'ORGANIZATION'), ('Brook', 'ORGANIZATION'), ('University', 'ORGANIZATION'), ('in', 'O'), ('NY', 'STATE_OR_PROVINCE')]

>>> from nltk.parse import CoreNLPParser
>>> tagger = CoreNLPParser(url='http://localhost:9000', tagtype='ner')
>>> tokens = 'Rami Eid is studying at Stony Brook University in NY'.split()
>>> 
>>> tagger.tag(tokens)
[('Rami', 'PERSON'), ('Eid', 'PERSON'), ('is', 'O'), ('studying', 'O'), ('at', 'O'), ('Stony', 'ORGANIZATION'), ('Brook', 'ORGANIZATION'), ('University', 'ORGANIZATION'), ('in', 'O'), ('NY', 'STATE_OR_PROVINCE')]

---

窗户 您可以使用

powershell

（您确实是这样做的）使用上述功能，但如果您喜欢单击鼠标

步骤1:从下载zip文件

第二步：解压

第3步：打开命令提示符并转到文件解压缩的文件夹

步骤4:运行命令：

pip3安装-U nltk

步骤5:现在运行命令：

java -mx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer -preload tokenize,ssplit,pos,lemma,ner,parse,depparse -status_port 9000 -port 9000 -timeout 15000 &

然后在Python3中：

>>> from nltk.parse import CoreNLPParser
>>> tagger = CoreNLPParser(url='http://localhost:9000', tagtype='ner')
>>> tokens = 'Rami Eid is studying at Stony Brook University in NY'.split()
>>> 
>>> tagger.tag(tokens)
[('Rami', 'PERSON'), ('Eid', 'PERSON'), ('is', 'O'), ('studying', 'O'), ('at', 'O'), ('Stony', 'ORGANIZATION'), ('Brook', 'ORGANIZATION'), ('University', 'ORGANIZATION'), ('in', 'O'), ('NY', 'STATE_OR_PROVINCE')]

>>> from nltk.parse import CoreNLPParser
>>> tagger = CoreNLPParser(url='http://localhost:9000', tagtype='ner')
>>> tokens = 'Rami Eid is studying at Stony Brook University in NY'.split()
>>> 
>>> tagger.tag(tokens)
[('Rami', 'PERSON'), ('Eid', 'PERSON'), ('is', 'O'), ('studying', 'O'), ('at', 'O'), ('Stony', 'ORGANIZATION'), ('Brook', 'ORGANIZATION'), ('University', 'ORGANIZATION'), ('in', 'O'), ('NY', 'STATE_OR_PROVINCE')]

---

谢谢你，因为这很有帮助。你能帮个忙吗？谢谢你，艾尔瓦。你能帮忙吗