sparknlp.annotator.stemmer#

Classes#

class Stemmer[source]#

Returns hard-stems out of words with the objective of retrieving the meaningful part of the word.

For extended examples of usage, see the Examples.

Input Annotation types	Output Annotation type
TOKEN	TOKEN

Parameters:

None

Examples

>>> import sparknlp
>>> from sparknlp.base import *
>>> from sparknlp.annotator import *
>>> from pyspark.ml import Pipeline
>>> documentAssembler = DocumentAssembler() \
...     .setInputCol("text") \
...     .setOutputCol("document")
>>> tokenizer = Tokenizer() \
...     .setInputCols(["document"]) \
...     .setOutputCol("token")
>>> stemmer = Stemmer() \
...     .setInputCols(["token"]) \
...     .setOutputCol("stem")
>>> pipeline = Pipeline().setStages([
...     documentAssembler,
...     tokenizer,
...     stemmer
... ])
>>> data = spark.createDataFrame([["Peter Pipers employees are picking pecks of pickled peppers."]]) \
...     .toDF("text")
>>> result = pipeline.fit(data).transform(data)
>>> result.selectExpr("stem.result").show(truncate = False)
+-------------------------------------------------------------+
|result                                                       |
+-------------------------------------------------------------+
|[peter, piper, employe, ar, pick, peck, of, pickl, pepper, .]|
+-------------------------------------------------------------+

inputAnnotatorTypes[source]#

outputAnnotatorType = 'token'[source]#

language[source]#

name = 'Stemmer'[source]#