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_st", "st") \
.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("Ntle le ho ba morena oa leboea, John Snow ke ngaka ea Lenyesemane ebile ke moetapele nts'etsopele ea anesthesia le bohloeki ba bongaka.")
...
val stopWords = StopWordsCleaner.pretrained("stopwords_st", "st")
.setInputCols(Array("token"))
.setOutputCol("cleanTokens")
val pipeline = new Pipeline().setStages(Array(document_assembler, tokenizer, stopWords))
val data = Seq("Ntle le ho ba morena oa leboea, John Snow ke ngaka ea Lenyesemane ebile ke moetapele nts'etsopele ea anesthesia le bohloeki ba bongaka.").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
text = ["""Ntle le ho ba morena oa leboea, John Snow ke ngaka ea Lenyesemane ebile ke moetapele nts'etsopele ea anesthesia le bohloeki ba bongaka."""]
stopword_df = nlu.load('st.stopwords').predict(text)
stopword_df[['cleanTokens']]
Results
[Row(annotatorType='token', begin=0, end=3, result='Ntle', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=14, end=19, result='morena', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=24, end=29, result='leboea', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=30, end=30, result=',', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=32, end=35, result='John', metadata={'sentence': '0'}),
...]
Model Information
| Model Name: | stopwords_st |
| Type: | stopwords |
| Compatibility: | Spark NLP 2.5.4+ |
| Edition: | Official |
| Input Labels: | [token] |
| Output Labels: | [cleanTokens] |
| Language: | st |
| Case sensitive: | false |
| License: | Open Source |
Data Source
The model is imported from https://github.com/WorldBrain/remove-stopwords