nlp_entity_ruler: Spark NLP EntityRulerApproach

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

Spark NLP EntityRulerApproach

Description

Spark ML estimator that See https://nlp.johnsnowlabs.com/docs/en/annotators#entityruler

Usage

nlp_entity_ruler(
  x,
  input_cols,
  output_col,
  case_sensitive = NULL,
  enable_pattern_regex = NULL,
  patterns_resource_path = NULL,
  patterns_resource_read_as = NULL,
  patterns_resource_options = NULL,
  storage_path = NULL,
  storage_ref = NULL,
  use_storage = NULL,
  uid = random_string("entity_ruler_")
)

Arguments

x	A spark_connection, ml_pipeline, or a tbl_spark.
input_cols	Input columns. String array.
output_col	Output column. String.
case_sensitive	Whether to ignore case in index lookups (Default depends on model)
enable_pattern_regex	Enables regex pattern match (Default: false).
patterns_resource_path	Resource in JSON or CSV format to map entities to patterns (Default: null).
patterns_resource_read_as	TEXT or SPARK_DATASET
patterns_resource_options	options passed to the reader. (Default: list("format" = "JSON"))
storage_path	Path to the external resource.
storage_ref	Unique identifier for storage (Default: this.uid)
use_storage	Whether to use RocksDB storage to serialize patterns (Default: true).
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.