python识别中文人名_使用Python在NLP中的命名实体识别中提取人名
我有一句话,我需要单独识别人名：
例如：
sentence = "Larry Page is an American business magnate and computer scientist who is the co-founder of Google, alongside Sergey Brin"
我使用下面的代码来识别NER.
from nltk import word_tokenize, pos_tag, ne_chunk
print(ne_chunk(pos_tag(word_tokenize(sentence))))
我收到的输出是：
(S
(PERSON Larry/NNP)
(ORGANIZATION Page/NNP)
is/VBZ
an/DT
(GPE American/JJ)
business/NN
magnate/NN
and/CC
computer/NN
scientist/NN
who/WP
is/VBZ
the/DT
co-founder/NN
of/IN
(GPE Google/NNP)
,/,
alongside/RB
(PERSON Sergey/NNP Brin/NNP))
我想提取所有人名,例如
Larry Page
Sergey Brin
为了达到这个目的,我对这个link进行了测试并尝试了这一点.
from nltk.tag.stanford import StanfordNERTagger
st = StanfordNERTagger('/usr/share/stanford-ner/classifiers/english.all.3class.distsim.crf.ser.gz','/usr/share/stanford-ner/stanford-ner.jar')
但是我继续得到这个错误：
LookupError: Could not find stanford-ner.jar jar file at /usr/share/stanford-ner/stanford-ner.jar
我在哪里可以下载这个文件？
如上所述,我期望以列表或字典的形式出现的结果是：
Larry Page
Sergey Brin
最佳答案 在龙
请仔细阅读：
了解解决方案,不要只是复制和粘贴.
TL; DR
在终端：
pip install -U nltk
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中
from nltk.tag.stanford import CoreNLPNERTagger
def get_continuous_chunks(tagged_sent):
continuous_chunk = []
current_chunk = []
for token, tag in tagged_sent:
if tag != "O":
current_chunk.append((token, tag))
else:
if current_chunk: # if the current chunk is not empty
continuous_chunk.append(current_chunk)
current_chunk = []
# Flush the final current_chunk into the continuous_chunk, if any.
if current_chunk:
continuous_chunk.append(current_chunk)
return continuous_chunk
stner = CoreNLPNERTagger()
tagged_sent = stner.tag('Rami Eid is studying at Stony Brook University in NY'.split())
named_entities = get_continuous_chunks(tagged_sent)
named_entities_str_tag = [(" ".join([token for token, tag in ne]), ne[0][1]) for ne in named_entities]
print(named_entities_str_tag)
[OUT]：
[('Rami Eid', 'PERSON'), ('Stony Brook University', 'ORGANIZATION'), ('NY', 'LOCATION')]