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  • John Snow Labs
  • May 09, 2022

Japanese Part of Speech Tagger (from KoichiYasuoka)

  • bert
  • pos
  • part_of_speech
  • ja
  • open_source

Description

Pretrained Part of Speech model model, uploaded to Hugging Face, adapted and imported into Spark NLP. bert-large-japanese-unidic-luw-upos is a Japanese model orginally trained by KoichiYasuoka.

Download Copy S3 URI

How to use

documentAssembler = DocumentAssembler() \
        .setInputCol("text") \
        .setOutputCol("document")

sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\
       .setInputCols(["document"])\
       .setOutputCol("sentence")

tokenizer = Tokenizer() \
    .setInputCols("sentence") \
    .setOutputCol("token")

tokenClassifier = BertForTokenClassification.pretrained("bert_pos_bert_large_japanese_unidic_luw_upos","ja") \
    .setInputCols(["sentence", "token"]) \
    .setOutputCol("pos")

pipeline = Pipeline(stages=[documentAssembler, sentenceDetector, tokenizer, tokenClassifier])

data = spark.createDataFrame([["Spark NLPが大好きです"]]).toDF("text")

result = pipeline.fit(data).transform(data)

val documentAssembler = new DocumentAssembler() 
          .setInputCol("text") 
          .setOutputCol("document")

val sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
       .setInputCols(Array("document"))
       .setOutputCol("sentence")

val tokenizer = new Tokenizer() 
    .setInputCols(Array("sentence"))
    .setOutputCol("token")

val tokenClassifier = BertForTokenClassification.pretrained("bert_pos_bert_large_japanese_unidic_luw_upos","ja") 
    .setInputCols(Array("sentence", "token")) 
    .setOutputCol("pos")

val pipeline = new Pipeline().setStages(Array(documentAssembler,sentenceDetector, tokenizer, tokenClassifier))

val data = Seq("Spark NLPが大好きです").toDF("text")

val result = pipeline.fit(data).transform(data)

Model Information

Model Name: bert_pos_bert_large_japanese_unidic_luw_upos
Compatibility: Spark NLP 3.4.2+
License: Open Source
Edition: Official
Input Labels: [document, token]
Output Labels: [ner]
Language: ja
Size: 1.3 GB
Case sensitive: true
Max sentence length: 128

References

  • https://huggingface.co/KoichiYasuoka/bert-large-japanese-unidic-luw-upos
  • https://universaldependencies.org/u/pos/
  • https://pypi.org/project/fugashi
  • https://pypi.org/project/unidic-lite
  • https://pypi.org/project/pytokenizations
  • http://id.nii.ac.jp/1001/00216223/
  • https://github.com/KoichiYasuoka/esupar