注意:此方法將只爲工作:
- NLTK v3.2.5(v3.2.6將有一個更簡單的接口)
- 斯坦福CoreNLP(版本> = 2016年10月31日)
首先,你必須獲取Java 8正確安裝第一,如果斯坦福CoreNLP工作在命令行中,NLTK v3.2.5斯坦福CoreNLP API是 如下。
注:你必須使用NLTK新CoreNLP API,開始在終端的CoreNLP服務器之前。
英語
在終端:
wget http://nlp.stanford.edu/software/stanford-corenlp-full-2016-10-31.zip
unzip stanford-corenlp-full-2016-10-31.zip && cd stanford-corenlp-full-2016-10-31
java -mx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer \
-preload tokenize,ssplit,pos,lemma,parse,depparse \
-status_port 9000 -port 9000 -timeout 15000
在Python:
>>> from nltk.tag.stanford import CoreNLPPOSTagger, CoreNLPNERTagger
>>> stpos, stner = CoreNLPPOSTagger(), CoreNLPNERTagger()
>>> stpos.tag('What is the airspeed of an unladen swallow ?'.split())
[(u'What', u'WP'), (u'is', u'VBZ'), (u'the', u'DT'), (u'airspeed', u'NN'), (u'of', u'IN'), (u'an', u'DT'), (u'unladen', u'JJ'), (u'swallow', u'VB'), (u'?', u'.')]
>>> stner.tag('Rami Eid is studying at Stony Brook University in NY'.split())
[(u'Rami', u'PERSON'), (u'Eid', u'PERSON'), (u'is', u'O'), (u'studying', u'O'), (u'at', u'O'), (u'Stony', u'ORGANIZATION'), (u'Brook', u'ORGANIZATION'), (u'University', u'ORGANIZATION'), (u'in', u'O'), (u'NY', u'O')]
中國
在終端:
wget http://nlp.stanford.edu/software/stanford-corenlp-full-2016-10-31.zip
unzip stanford-corenlp-full-2016-10-31.zip && cd stanford-corenlp-full-2016-10-31
wget http://nlp.stanford.edu/software/stanford-chinese-corenlp-2016-10-31-models.jar
wget https://raw.githubusercontent.com/stanfordnlp/CoreNLP/master/src/edu/stanford/nlp/pipeline/StanfordCoreNLP-chinese.properties
java -Xmx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer \
-serverProperties StanfordCoreNLP-chinese.properties \
-preload tokenize,ssplit,pos,lemma,ner,parse \
-status_port 9001 -port 9001 -timeout 15000
在Python
>>> from nltk.tag.stanford import CoreNLPPOSTagger, CoreNLPNERTagger
>>> from nltk.tokenize.stanford import CoreNLPTokenizer
>>> stpos, stner = CoreNLPPOSTagger('http://localhost:9001'), CoreNLPNERTagger('http://localhost:9001')
>>> sttok = CoreNLPTokenizer('http://localhost:9001')
>>> sttok.tokenize(u'我家沒有電腦。')
['我家', '沒有', '電腦', '。']
# Without segmentation (input to`raw_string_parse()` is a list of single char strings)
>>> stpos.tag(u'我家沒有電腦。')
[('我', 'PN'), ('家', 'NN'), ('沒', 'AD'), ('有', 'VV'), ('電', 'NN'), ('腦', 'NN'), ('。', 'PU')]
# With segmentation
>>> stpos.tag(sttok.tokenize(u'我家沒有電腦。'))
[('我家', 'NN'), ('沒有', 'VE'), ('電腦', 'NN'), ('。', 'PU')]
# Without segmentation (input to`raw_string_parse()` is a list of single char strings)
>>> stner.tag(u'奧巴馬與邁克爾·傑克遜一起去雜貨店購物。')
[('奧', 'GPE'), ('巴', 'GPE'), ('馬', 'GPE'), ('與', 'O'), ('邁', 'O'), ('克', 'PERSON'), ('爾', 'PERSON'), ('·', 'O'), ('傑', 'O'), ('克', 'O'), ('遜', 'O'), ('一', 'NUMBER'), ('起', 'O'), ('去', 'O'), ('雜', 'O'), ('貨', 'O'), ('店', 'O'), ('購', 'O'), ('物', 'O'), ('。', 'O')]
# With segmentation
>>> stner.tag(sttok.tokenize(u'奧巴馬與邁克爾·傑克遜一起去雜貨店購物。'))
[('奧巴馬', 'PERSON'), ('與', 'O'), ('邁克爾·傑克遜', 'PERSON'), ('一起', 'O'), ('去', 'O'), ('雜貨店', 'O'), ('購物', 'O'), ('。', 'O')]
德國
在終端:
wget http://nlp.stanford.edu/software/stanford-corenlp-full-2016-10-31.zip
unzip stanford-corenlp-full-2016-10-31.zip && cd stanford-corenlp-full-2016-10-31
wget http://nlp.stanford.edu/software/stanford-german-corenlp-2016-10-31-models.jar
wget https://raw.githubusercontent.com/stanfordnlp/CoreNLP/master/src/edu/stanford/nlp/pipeline/StanfordCoreNLP-german.properties
java -Xmx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer \
-serverProperties StanfordCoreNLP-german.properties \
-preload tokenize,ssplit,pos,ner,parse \
-status_port 9002 -port 9002 -timeout 15000
在Python:
>>> from nltk.tag.stanford import CoreNLPPOSTagger, CoreNLPNERTagger
>>> stpos, stner = CoreNLPPOSTagger('http://localhost:9002'), CoreNLPNERTagger('http://localhost:9002')
>>> stpos.tag('Ich bin schwanger'.split())
[('Ich', 'PPER'), ('bin', 'VAFIN'), ('schwanger', 'ADJD')]
>>> stner.tag('Donald Trump besuchte Angela Merkel in Berlin.'.split())
[('Donald', 'I-PER'), ('Trump', 'I-PER'), ('besuchte', 'O'), ('Angela', 'I-PER'), ('Merkel', 'I-PER'), ('in', 'O'), ('Berlin', 'I-LOC'), ('.', 'O')]
西班牙語
在終端:
wget http://nlp.stanford.edu/software/stanford-corenlp-full-2016-10-31.zip
unzip stanford-corenlp-full-2016-10-31.zip && cd stanford-corenlp-full-2016-10-31
wget http://nlp.stanford.edu/software/stanford-spanish-corenlp-2016-10-31-models.jar
wget https://raw.githubusercontent.com/stanfordnlp/CoreNLP/master/src/edu/stanford/nlp/pipeline/StanfordCoreNLP-spanish.properties
java -Xmx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer \
-serverProperties StanfordCoreNLP-spanish.properties \
-preload tokenize,ssplit,pos,ner,parse \
-status_port 9003 -port 9003 -timeout 15000
在Python:
>>> from nltk.tag.stanford import CoreNLPPOSTagger, CoreNLPNERTagger
>>> stpos, stner = CoreNLPPOSTagger('http://localhost:9003'), CoreNLPNERTagger('http://localhost:9003')
>>> stner.tag(u'Barack Obama salió con Michael Jackson .'.split())
[(u'Barack', u'PERS'), (u'Obama', u'PERS'), (u'sali\xf3', u'O'), (u'con', u'O'), (u'Michael', u'PERS'), (u'Jackson', u'PERS'), (u'.', u'O')]
>>> stpos.tag(u'Barack Obama salió con Michael Jackson .'.split())
[(u'Barack', u'np00000'), (u'Obama', u'np00000'), (u'sali\xf3', u'vmis000'), (u'con', u'sp000'), (u'Michael', u'np00000'), (u'Jackson', u'np00000'), (u'.', u'fp')]
法語
在終端:
wget http://nlp.stanford.edu/software/stanford-corenlp-full-2016-10-31.zip
unzip stanford-corenlp-full-2016-10-31.zip && cd stanford-corenlp-full-2016-10-31
wget http://nlp.stanford.edu/software/stanford-french-corenlp-2016-10-31-models.jar
wget https://raw.githubusercontent.com/stanfordnlp/CoreNLP/master/src/edu/stanford/nlp/pipeline/StanfordCoreNLP-french.properties
java -Xmx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer \
-serverProperties StanfordCoreNLP-french.properties \
-preload tokenize,ssplit,pos,parse \
-status_port 9004 -port 9004 -timeout 15000
在Python:
>>> from nltk.tag.stanford import CoreNLPPOSTagger
>>> stpos = CoreNLPPOSTagger('http://localhost:9004')
>>> stpos.tag('Je suis enceinte'.split())
[(u'Je', u'CLS'), (u'suis', u'V'), (u'enceinte', u'NC')]
阿拉伯
在終端:
wget http://nlp.stanford.edu/software/stanford-corenlp-full-2016-10-31.zip
unzip stanford-corenlp-full-2016-10-31.zip && cd stanford-corenlp-full-2016-10-31
wget http://nlp.stanford.edu/software/stanford-arabic-corenlp-2016-10-31-models.jar
wget https://raw.githubusercontent.com/stanfordnlp/CoreNLP/master/src/edu/stanford/nlp/pipeline/StanfordCoreNLP-arabic.properties
java -Xmx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer \
-serverProperties StanfordCoreNLP-french.properties \
-preload tokenize,ssplit,pos,parse \
-status_port 9005 -port 9005 -timeout 15000
在Python:
>>> from nltk.tag.stanford import CoreNLPPOSTagger
>>> from nltk.tokenize.stanford import CoreNLPTokenizer
>>> sttok = CoreNLPTokenizer('http://localhost:9005')
>>> stpos = CoreNLPPOSTagger('http://localhost:9005')
>>> text = u'انا حامل'
>>> stpos.tag(sttok.tokenize(text))
[('انا', 'DET'), ('حامل', 'NC')]
的'CLASSPATH'應該是一個目錄(或幾個),而不是一個文件水珠。將它改爲'「C:/ Users/User/Folder/stanford-segmenter-2017-06-09」'看看是否有幫助。但可能還有其他問題,我不知道。 – alexis
這似乎沒有幫助,但謝謝你。我可能試圖做太多而不瞭解事情是如何建立的。現在,我會研究使用不同的程序或軟件包。顯然,「解霸」是另一種Python選擇,無需使用Java調用。 – Savi
適合自己。但是你有沒有在nltk的github網站上看過[安裝第三方軟件](https://github.com/nltk/nltk/wiki/Installing-Third-Party-Software)? (我不知道爲什麼這個頁面沒有出現在nltk的常見問題頁面中) – alexis