Description
This model removes ‘stop words’ from text. Stop words are words so common that they can be removed without significantly altering the meaning of a text. Removing stop words is useful when one wants to deal with only the most semantically important words in a text, and ignore words that are rarely semantically relevant, such as articles and prepositions.
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How to use
...
stop_words = StopWordsCleaner.pretrained("stopwords_sv", "sv") \
.setInputCols(["token"]) \
.setOutputCol("cleanTokens")
nlp_pipeline = Pipeline(stages=[document_assembler, tokenizer, stop_words])
light_pipeline = LightPipeline(nlp_pipeline.fit(spark.createDataFrame([['']]).toDF("text")))
results = light_pipeline.fullAnnotate("Förutom att vara kungen i norr är John Snow en engelsk läkare och en ledare inom utveckling av anestesi och medicinsk hygien.")
...
val stopWords = StopWordsCleaner.pretrained("stopwords_sv", "sv")
.setInputCols(Array("token"))
.setOutputCol("cleanTokens")
val pipeline = new Pipeline().setStages(Array(document_assembler, tokenizer, stopWords))
val data = Seq("Förutom att vara kungen i norr är John Snow en engelsk läkare och en ledare inom utveckling av anestesi och medicinsk hygien.").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
text = ["""Förutom att vara kungen i norr är John Snow en engelsk läkare och en ledare inom utveckling av anestesi och medicinsk hygien."""]
stopword_df = nlu.load('sv.stopwords').predict(text)
stopword_df[['cleanTokens']]
Results
[Row(annotatorType='token', begin=0, end=6, result='Förutom', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=17, end=22, result='kungen', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=26, end=29, result='norr', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=31, end=32, result='är', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=34, end=37, result='John', metadata={'sentence': '0'}),
...]
Model Information
Model Name: | stopwords_sv |
Type: | stopwords |
Compatibility: | Spark NLP 2.5.4+ |
Edition: | Official |
Input Labels: | [token] |
Output Labels: | [cleanTokens] |
Language: | sv |
Case sensitive: | false |
License: | Open Source |
Data Source
The model is imported from https://github.com/WorldBrain/remove-stopwords