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.
How to use
...
stop_words = StopWordsCleaner.pretrained("stopwords_fi", "fi") \
.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("Sen lisäksi, että hän on pohjoisen kuningas, John Snow on englantilainen lääkäri ja johtava anestesian ja lääketieteellisen hygienian kehittämisessä.")
...
val stopWords = StopWordsCleaner.pretrained("stopwords_fi", "fi")
.setInputCols(Array("token"))
.setOutputCol("cleanTokens")
val pipeline = new Pipeline().setStages(Array(document_assembler, tokenizer, stopWords))
val result = pipeline.fit(Seq.empty["Sen lisäksi, että hän on pohjoisen kuningas, John Snow on englantilainen lääkäri ja johtava anestesian ja lääketieteellisen hygienian kehittämisessä."].toDS.toDF("text")).transform(data)
Results
[Row(annotatorType='token', begin=11, end=11, result=',', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=25, end=33, result='pohjoisen', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=35, end=42, result='kuningas', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=43, end=43, result=',', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=45, end=48, result='John', metadata={'sentence': '0'}),
...]
Model Information
| Model Name: | stopwords_fi |
| Type: | stopwords |
| Compatibility: | Spark NLP 2.5.4+ |
| Edition: | Official |
| Input Labels: | [token] |
| Output Labels: | [cleanTokens] |
| Language: | fi |
| Case sensitive: | false |
| License: | Open Source |
Data Source
The model is imported from https://github.com/WorldBrain/remove-stopwords