如何训练spacy在不指定其他标签的情况下识别标签？

import spacy

nlp = spacy.blank("en")

ner = nlp.create_pipe("ner")
nlp.add_pipe(ner)

for label in ["PERSON", "LOC", "ORG"]:
    ner.add_label(label)

# 准备训练数据
train_data = [
    ("John Doe is going to New York.", {"entities": [(0, 8, "PERSON"), (23, 31, "LOC")]}),
    ("Apple Inc. is a technology company.", {"entities": [(0, 9, "ORG")]}),
    # 其他训练样本
]

# 开始训练
for text, annotations in train_data:
    doc = nlp.make_doc(text)
    example = spacy.training.Example.from_dict(doc, annotations)
    nlp.update([example], losses={})

# 保存训练好的模型
nlp.to_disk("trained_model")

# 加载训练好的模型
nlp = spacy.load("trained_model")

# 预测实体
text = "John Doe is working at Apple Inc."
doc = nlp(text)
for ent in doc.ents:
    print(ent.text, ent.label_)