如何使用 NLTK 获取时间和日期或特定产品名称？
How to get time and date or specific product name using NLTK?
doc = '''Andrew Yan-Tak Ng is a Chinese American computer scientist.He is the former chief scientist at Baidu, where he led the company's
Artificial Intelligence Group. He is an adjunct professor (formerly associate professor) at Stanford University. Ng is also the co-founder
and chairman at Coursera, an online education platform. Andrew was born in the UK on 27th Sep 2.30pm 1976. His parents were both from Hong Kong.'''
# tokenize doc
tokenized_doc = nltk.word_tokenize (doc)
# tag sentences and use nltk's Named Entity Chunker
tagged_sentences = nltk.pos_tag (tokenized_doc)
ne_chunked_sents = nltk.ne_chunk (tagged_sentences)
当你处理和提取卡盘时..我看到我们只得到
[('Andrew', 'PERSON'), ('Chinese', 'GPE'), ('American', 'GPE'), ('Baidu', 'ORGANIZATION'), ("company's Artificial Intelligence Group", 'ORGANIZATION'), ('Stanford University', 'ORGANIZATION'), ('Coursera', 'ORGANIZATION'), ( 'Andrew', 'PERSON'), ('UK', 'ORGANIZATION'), ('Hong Kong', 'GPE')]
我也需要获取时间和日期吗？
请建议...
谢谢。
您需要更复杂的标注器，例如斯坦福的命名实体标注器。安装和配置后，您可以 运行 它：
from nltk.tag import StanfordNERTagger
from nltk.tokenize import word_tokenize
stanfordClassifier = '/path/to/classifier/classifiers/english.muc.7class.distsim.crf.ser.gz'
stanfordNerPath = '/path/to/jar/stanford-ner/stanford-ner.jar'
st = StanfordNERTagger(stanfordClassifier, stanfordNerPath, encoding='utf8')
doc = '''Andrew Yan-Tak Ng is a Chinese American computer scientist.He is the former chief scientist at Baidu, where he led the company's Artificial Intelligence Group. He is an adjunct professor (formerly associate professor) at Stanford University. Ng is also the co-founder and chairman at Coursera, an online education platform. Andrew was born in the UK on 27th Sep 2.30pm 1976. His parents were both from Hong Kong.'''
result = st.tag(word_tokenize(doc))
date_word_tags = [wt for wt in result if wt[1] == 'DATE' or wt[1] == 'ORGANIZATION']
print date_word_tags
输出的位置：
[(u'Artificial', u'ORGANIZATION'), (u'Intelligence', u'ORGANIZATION'), (u'Group', u'ORGANIZATION'), (u'Stanford', u'ORGANIZATION'), (u'University', u'ORGANIZATION'), (u'Coursera', u'ORGANIZATION'), (u'27th', u'DATE'), (u'Sep', u'DATE'), (u'2.30pm', u'DATE'), (u'1976', u'DATE')]
在尝试安装和设置所有内容时，您可能会 运行 遇到一些问题，但我认为这是值得的。
如果有帮助请告诉我。
doc = '''Andrew Yan-Tak Ng is a Chinese American computer scientist.He is the former chief scientist at Baidu, where he led the company's
Artificial Intelligence Group. He is an adjunct professor (formerly associate professor) at Stanford University. Ng is also the co-founder
and chairman at Coursera, an online education platform. Andrew was born in the UK on 27th Sep 2.30pm 1976. His parents were both from Hong Kong.'''
# tokenize doc
tokenized_doc = nltk.word_tokenize (doc)
# tag sentences and use nltk's Named Entity Chunker
tagged_sentences = nltk.pos_tag (tokenized_doc)
ne_chunked_sents = nltk.ne_chunk (tagged_sentences)
当你处理和提取卡盘时..我看到我们只得到 [('Andrew', 'PERSON'), ('Chinese', 'GPE'), ('American', 'GPE'), ('Baidu', 'ORGANIZATION'), ("company's Artificial Intelligence Group", 'ORGANIZATION'), ('Stanford University', 'ORGANIZATION'), ('Coursera', 'ORGANIZATION'), ( 'Andrew', 'PERSON'), ('UK', 'ORGANIZATION'), ('Hong Kong', 'GPE')]
我也需要获取时间和日期吗？ 请建议... 谢谢。
您需要更复杂的标注器，例如斯坦福的命名实体标注器。安装和配置后，您可以 运行 它：
from nltk.tag import StanfordNERTagger
from nltk.tokenize import word_tokenize
stanfordClassifier = '/path/to/classifier/classifiers/english.muc.7class.distsim.crf.ser.gz'
stanfordNerPath = '/path/to/jar/stanford-ner/stanford-ner.jar'
st = StanfordNERTagger(stanfordClassifier, stanfordNerPath, encoding='utf8')
doc = '''Andrew Yan-Tak Ng is a Chinese American computer scientist.He is the former chief scientist at Baidu, where he led the company's Artificial Intelligence Group. He is an adjunct professor (formerly associate professor) at Stanford University. Ng is also the co-founder and chairman at Coursera, an online education platform. Andrew was born in the UK on 27th Sep 2.30pm 1976. His parents were both from Hong Kong.'''
result = st.tag(word_tokenize(doc))
date_word_tags = [wt for wt in result if wt[1] == 'DATE' or wt[1] == 'ORGANIZATION']
print date_word_tags
输出的位置：
[(u'Artificial', u'ORGANIZATION'), (u'Intelligence', u'ORGANIZATION'), (u'Group', u'ORGANIZATION'), (u'Stanford', u'ORGANIZATION'), (u'University', u'ORGANIZATION'), (u'Coursera', u'ORGANIZATION'), (u'27th', u'DATE'), (u'Sep', u'DATE'), (u'2.30pm', u'DATE'), (u'1976', u'DATE')]
在尝试安装和设置所有内容时，您可能会 运行 遇到一些问题，但我认为这是值得的。
如果有帮助请告诉我。