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_pt", "pt") \
.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("Além de ser o rei do norte, John Snow é um médico inglês e líder no desenvolvimento de anestesia e higiene médica.")
...
val stopWords = StopWordsCleaner.pretrained("stopwords_pt", "pt")
.setInputCols(Array("token"))
.setOutputCol("cleanTokens")
val pipeline = new Pipeline().setStages(Array(document_assembler, tokenizer, stopWords))
val data = Seq("Além de ser o rei do norte, John Snow é um médico inglês e líder no desenvolvimento de anestesia e higiene médica.").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
text = ["""Além de ser o rei do norte, John Snow é um médico inglês e líder no desenvolvimento de anestesia e higiene médica."""]
stopword_df = nlu.load('pt.stopwords').predict(text)
stopword_df[['cleanTokens']]
Results
[Row(annotatorType='token', begin=14, end=16, result='rei', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=21, end=25, result='norte', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=26, end=26, result=',', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=28, end=31, result='John', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=33, end=36, result='Snow', metadata={'sentence': '0'}),
...]
Model Information
| Model Name: | stopwords_pt |
| Type: | stopwords |
| Compatibility: | Spark NLP 2.5.4+ |
| Edition: | Official |
| Input Labels: | [token] |
| Output Labels: | [cleanTokens] |
| Language: | pt |
| Case sensitive: | false |
| License: | Open Source |
Data Source
The model is imported from https://github.com/WorldBrain/remove-stopwords