如何使用Spacy合并相同的连续实体类型

import spacy

# 加载Spacy的英文模型
nlp = spacy.load('en_core_web_sm')

text = "Apple Inc. was founded by Steve Jobs, Steve Wozniak, and Ronald Wayne. Apple Inc. is headquartered in Cupertino, California."

# 对文本进行实体识别
doc = nlp(text)

merged_entities = []
current_entity = None

for token in doc:
    if token.ent_type_ != "":
        if current_entity is None:
            current_entity = token
        elif token.ent_type_ == current_entity.ent_type_:
            current_entity = doc[current_entity.i:token.i+1]
        else:
            merged_entities.append(current_entity)
            current_entity = token
    else:
        if current_entity is not None:
            merged_entities.append(current_entity)
            current_entity = None

# 处理最后一个实体
if current_entity is not None:
    merged_entities.append(current_entity)

for entity in merged_entities:
    print(entity.text, entity.label_)