基于Python的Stanford-NLP实体识别

Question

我正在使用Python使用Stanford Core NLP。我从here获取代码。
代码如下：

from stanfordcorenlp import StanfordCoreNLP
import logging
import json


class StanfordNLP:
def __init__(self, host='http://localhost', port=9000):
    self.nlp = StanfordCoreNLP(host, port=port,
                               timeout=30000 , quiet=True, logging_level=logging.DEBUG)
    self.props = {
        'annotators': 'tokenize,ssplit,pos,lemma,ner,parse,depparse,dcoref,relation,sentiment',
        'pipelineLanguage': 'en',
        'outputFormat': 'json'
    }

def word_tokenize(self, sentence):
    return self.nlp.word_tokenize(sentence)

def pos(self, sentence):
    return self.nlp.pos_tag(sentence)

def ner(self, sentence):
    return self.nlp.ner(sentence)

def parse(self, sentence):
    return self.nlp.parse(sentence)

def dependency_parse(self, sentence):
    return self.nlp.dependency_parse(sentence)

def annotate(self, sentence):
    return json.loads(self.nlp.annotate(sentence, properties=self.props))

@staticmethod
def tokens_to_dict(_tokens):
    tokens = defaultdict(dict)
    for token in _tokens:
        tokens[int(token['index'])] = {
            'word': token['word'],
            'lemma': token['lemma'],
            'pos': token['pos'],
            'ner': token['ner']
        }
    return tokens

if __name__ == '__main__':
sNLP = StanfordNLP()
text = r'China on Wednesday issued a $50-billion list of U.S. goods  including soybeans and small aircraft for possible tariff hikes in an escalating technology dispute with Washington that companies worry could set back the global economic recovery.The country\'s tax agency gave no date for the 25 percent increase...'
ANNOTATE =  sNLP.annotate(text)
POS = sNLP.pos(text)
TOKENS = sNLP.word_tokenize(text)
NER = sNLP.ner(text)
PARSE = sNLP.parse(text)
DEP_PARSE = sNLP.dependency_parse(text)    

我只对保存在变量NER中的实体识别感兴趣。命令NER给出以下结果

如果我在Stanford Website上运行，那么NER的输出是

我的Python代码有两个问题：

1.“$”和“500亿”应合并并命名为单个实体。 类似地，我希望“25”和“percent”作为单个实体，因为它显示在在线斯坦福输出中。
2。在我的输出中，“华盛顿”显示为州，“中国”显示为国家。我希望他们都显示为'Loc'在斯坦福网站输出。这个问题的可能解决办法在于documentation。

但我不知道我用的是哪种模式，以及如何改变模式。在

Answer 1

这里有个方法可以解决这个问题

请务必下载Stanford CoreNLP 3.9.1和必要的模型JAR

在此文件“ner”中设置服务器属性-服务器.属性““

annotators = tokenize,ssplit,pos,lemma,ner
ner.applyFineGrained = false

使用以下命令启动服务器：

^{pr2}$

请确保已安装此Python包：

https://github.com/stanfordnlp/python-stanford-corenlp

运行以下Python代码：

import corenlp
client = corenlp.CoreNLPClient(start_server=False, annotators=["tokenize", "ssplit", "pos", "lemma", "ner"])
sample_text = "Joe Smith was born in Hawaii."
ann = client.annotate(sample_text)
for mention in ann.sentence[0].mentions:
    print([x.word for x in ann.sentence[0].token[mention.tokenStartInSentenceInclusive:mention.tokenEndInSentenceExclusive]])

以下是实体实体实体中可用的所有字段：

sentenceIndex: 0
tokenStartInSentenceInclusive: 5
tokenEndInSentenceExclusive: 7
ner: "MONEY"
normalizedNER: "$5.0E10"
entityType: "MONEY"