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_eo", "eo") \
.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("Krom esti la norda reĝo, John Snow estas angla kuracisto kaj gvidanto en la disvolviĝo de anestezo kaj medicina higieno.")
...
val stopWords = StopWordsCleaner.pretrained("stopwords_eo", "eo")
.setInputCols(Array("token"))
.setOutputCol("cleanTokens")
val pipeline = new Pipeline().setStages(Array(document_assembler, tokenizer, stopWords))
val data = Seq("Krom esti la norda reĝo, John Snow estas angla kuracisto kaj gvidanto en la disvolviĝo de anestezo kaj medicina higieno.").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
text = ["""Krom esti la norda reĝo, John Snow estas angla kuracisto kaj gvidanto en la disvolviĝo de anestezo kaj medicina higieno."""]
stopword_df = nlu.load('eo.stopwords').predict(text)
stopword_df[["cleanTokens"]]
Results
[Row(annotatorType='token', begin=0, end=3, result='Krom', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=5, end=8, result='esti', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=13, end=17, result='norda', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=19, end=22, result='reĝo', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=23, end=23, result=',', metadata={'sentence': '0'}),
...]
Model Information
| Model Name: | stopwords_eo |
| Type: | stopwords |
| Compatibility: | Spark NLP 2.5.4+ |
| Edition: | Official |
| Input Labels: | [token] |
| Output Labels: | [cleanTokens] |
| Language: | eo |
| Case sensitive: | false |
| License: | Open Source |
Data Source
The model is imported from https://github.com/WorldBrain/remove-stopwords