在spaCy中進行文本規范化可以通過以下步驟實現：
import spacy
from spacy.lemmatizer import Lemmatizer
from spacy.lookups import Lookups
nlp = spacy.load('en_core_web_sm')
lookups = Lookups()
lemmatizer = Lemmatizer(lookups)
def normalize_text(text):
doc = nlp(text)
normalized_text = []
for token in doc:
if not token.is_stop and not token.is_punct:
normalized_text.append(lemmatizer(token.text, token.pos_)[0])
return ' '.join(normalized_text)
text = "The quick brown foxes are jumping over the lazy dogs."
normalized_text = normalize_text(text)
print(normalized_text)
通過以上步驟，我們可以使用spaCy對文本進行規范化處理，包括詞形還原、去除停用詞等操作，以提高文本處理的效果。
