如何将简单训练样式的数据转换为spaCy的命令行JSON格式？

import spacy

nlp = spacy.blank("en")
ner = nlp.create_pipe("ner")
ner.add_label("PRODUCT")
nlp.add_pipe(ner)

with open("training_data.txt", "r") as file:
    training_data = file.read()

from spacy.gold import GoldParse

examples = []
for line in training_data.split("\n"):
    text, entities = line.split("\t")
    entities = entities.split(",")
    entities = [(int(start), int(end), "PRODUCT") for start, end in entities]
    examples.append((text, GoldParse(nlp.make_doc(text), entities=entities)))

nlp.begin_training()
for text, annotations in examples:
    nlp.update([text], [annotations])

nlp.to_disk("trained_model")

import spacy.convert

spacy.convert.export(nlp, "json", "trained_model", "output_model.json")