Python-Spacy 实现英文命名实体识别(NER)_spacy实体识别

环境准备

# 清华源安装spacy包
pip install -U spacy -i https://pypi.tuna.tsinghua.edu.cn/simple
python -m spacy download en_core_web_sm
# 如果安装失败可以使用手动安装的方法
# wget https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.6.0/en_core_web_sm-3.6.0-py3-none-any.whl
# pip install en_core_web_sm-3.6.0-py3-none-any.whl

代码实现

import spacy
 
# Load English tokenizer, tagger, parser and NER
nlp = spacy.load("en_core_web_sm")
 
# Process whole documents
text = ("When Sebastian Thrun started working on self-driving cars at "
        "Google in 2007, few people outside of the company took him "
        "seriously. “I can tell you very senior CEOs of major American "
        "car companies would shake my hand and turn away because I wasn’t "
        "worth talking to,” said Thrun, in an interview with Recode earlier "
        "this week.")
doc = nlp(text)
 
# Analyze syntax
print("Noun phrases:", [chunk.text for chunk in doc.noun_chunks])
print("Verbs:", [token.lemma_ for token in doc if token.pos_ == "VERB"])
 
# Find named entities, phrases and concepts
for entity in doc.ents:
    print(entity.text, entity.label_)