nlp_assertion_filterer: Spark NLP AssertionFilterer

In r-spark/sparknlp: R Interface to John Snow Labs Spark NLP

Spark NLP AssertionFilterer

Description

Spark ML transformer that will allow you to filter out the named entities by the list of acceptable assertion statuses. This annotator would be quite handy if you want to set a white list for the acceptable assertion statuses like present or conditional; and do not want absent conditions get out of your pipeline. See https://nlp.johnsnowlabs.com/docs/en/licensed_release_notes#3-assertionfilterer

Usage

nlp_assertion_filterer(
  x,
  input_cols,
  output_col,
  criteria = NULL,
  whitelist = NULL,
  regex = NULL,
  uid = random_string("assertion_filterer_")
)

Arguments

x	A spark_connection, ml_pipeline, or a tbl_spark.
input_cols	Input columns. String array.
output_col	Output column. String.
criteria	isin or regex
whitelist	If defined, list of entities to process.
regex	If defined, list of entities to process.
uid	A character string used to uniquely identify the ML estimator.

Value

The object returned depends on the class of x.

• spark_connection: When x is a spark_connection, the function returns an instance of a ml_estimator object. The object contains a pointer to a Spark Estimator object and can be used to compose Pipeline objects.

• ml_pipeline: When x is a ml_pipeline, the function returns a ml_pipeline with the NLP estimator appended to the pipeline.

• tbl_spark: When x is a tbl_spark, an estimator is constructed then immediately fit with the input tbl_spark, returning an NLP model.

r-spark/sparknlp documentation built on Oct. 15, 2022, 10:50 a.m.