如何使用sparknlp中的注释器处理文本文件

from sparknlp.base import *
from sparknlp.annotator import *
from pyspark.ml import Pipeline

from pyspark.sql import SparkSession

spark = SparkSession.builder \
    .appName("SparkNLP") \
    .getOrCreate()

data = spark.read.text("path_to_text_file")

document_assembler = DocumentAssembler() \
    .setInputCol("value") \
    .setOutputCol("document")

tokenizer = Tokenizer() \
    .setInputCols(["document"]) \
    .setOutputCol("tokenized")

# 添加其他需要的注释器，如词性标注器、命名实体识别器等

# 创建注释器管道
pipeline = Pipeline(stages=[
    document_assembler,
    tokenizer,
    # 添加其他注释器到管道
])

result = pipeline.fit(data).transform(data)

result.show()