我设计了一个红色字体动词短语的代码并将其输出为 HTML。
from __future__ import unicode_literals
import spacy,en_core_web_sm
import textacy
import codecs
nlp = en_core_web_sm.load()
sentence = 'The author is writing a new book. The dog is barking.'
pattern = r'<VERB>?<ADV>*<VERB>+'
doc = textacy.Doc(sentence, lang='en_core_web_sm')
lists = textacy.extract.pos_regex_matches(doc, pattern)
with open("my.html","w") as fp:
for list in lists:
search_word = (list.text)
fp.write(sentence.replace(search_word, '<span style="color: red">{}</span>'.format(search_word)))
电流输出
The author **is writing** a new book. The dog is barking.The author is writing a new book. The dog **is barking.**
该句子重复两次，第一次是书写，最后一次是检测到吠叫。
预期输出：
The author **is writing** a new book. The dog **is barking.**
在将其发送到列表检查之前我是否应该进行句子标记化？请帮忙？
找到了另一种更合乎逻辑的方式。与其在整个句子中替换，不如在具有模式的句子中替换。
with open("my.html","w") as fp:
for _list in lists:
search_word = (_list.text)
containing_sentence = [i for i in sentence.split('.') if str(search_word) in str(i)][0]
fp.write(containing_sentence.replace(search_word, '<span style="color: red">{}</span>'.format(search_word)))
上面的代码将分别写出句子。如果您想将其作为一个句子来执行，请将修改附加到列表中并在写入文件之前将它们连接起来，如下所示。
mod_sentence = []
for _list in lists:
search_word = (_list.text)
containing_sentence = [i for i in sentence.split('.') if str(search_word) in str(i)][0]+'.'
mod_sentence.append(containing_sentence.replace(search_word, '<span style="color: red">{}</span>'.format(search_word)))
with open("my.html","w") as fp:
fp.write(''.join(mod_sentence))
希望这可以帮助！干杯!
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