Stop Words Cleaner for Hausa

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_ha", "ha") \
.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("Ban da kasancewarsa sarkin arewa, John Snow likita ne na Ingilishi kuma jagora a ci gaban maganin sa barci da tsabtar lafiya.")
...
val stopWords = StopWordsCleaner.pretrained("stopwords_ha", "ha")
.setInputCols(Array("token"))
.setOutputCol("cleanTokens")
val pipeline = new Pipeline().setStages(Array(document_assembler, tokenizer, stopWords))
val data = Seq("Ban da kasancewarsa sarkin arewa, John Snow likita ne na Ingilishi kuma jagora a ci gaban maganin sa barci da tsabtar lafiya.").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu

text = ["""Ban da kasancewarsa sarkin arewa, John Snow likita ne na Ingilishi kuma jagora a ci gaban maganin sa barci da tsabtar lafiya."""]
stopword_df = nlu.load('ha.stopwords').predict(text)
stopword_df[['cleanTokens']]

Results

[Row(annotatorType='token', begin=7, end=18, result='kasancewarsa', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=20, end=25, result='sarkin', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=27, end=31, result='arewa', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=32, end=32, result=',', metadata={'sentence': '0'}),
Row(annotatorType='token', begin=34, end=37, result='John', metadata={'sentence': '0'}),
...]

Model Information

Model Name: stopwords_ha
Type: stopwords
Compatibility: Spark NLP 2.5.4+
Edition: Official
Input Labels: [token]
Output Labels: [cleanTokens]
Language: ha
Case sensitive: false
License: Open Source

Data Source

The model is imported from https://github.com/WorldBrain/remove-stopwords