nlp_lemmatizer: Spark NLP Lemmatizer

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

Spark NLP Lemmatizer

Description

Spark ML estimator that retrieves lemmas out of words with the objective of returning a base dictionary word See https://nlp.johnsnowlabs.com/docs/en/annotators#lemmatizer

Usage

nlp_lemmatizer(
  x,
  input_cols,
  output_col,
  dictionary_path = NULL,
  dictionary_key_delimiter = "->",
  dictionary_value_delimiter = "\t",
  dictionary_read_as = "TEXT",
  dictionary_options = list(format = "text"),
  uid = random_string("lemmatizer_")
)

Arguments

x	A spark_connection, ml_pipeline, or a tbl_spark.
input_cols	Input columns. String array.
output_col	Output column. String.
dictionary_path	Path to lemma dictionary, in lemma vs possible words format.
dictionary_key_delimiter	key delimiter in the dictionary file
dictionary_value_delimiter	value delimiter in the dictionary file
dictionary_read_as	readAs TEXT or SPARK_DATASET
dictionary_options	options passed to the spark reader if read_as is SPARK_DATASET
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 a default pretrained NLP model 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.