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  • John Snow Labs
  • May 17, 2022

Amharic Named Entity Recognition (from mbeukman)

  • xlm_roberta
  • ner
  • token_classification
  • am
  • open_source

Description

Pretrained Named Entity Recognition model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. xlm-roberta-base-finetuned-ner-amharic is a Amharic model orginally trained by mbeukman.

Predicted Entities

PER, ORG, LOC, DATE

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 = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic","am") \
    .setInputCols(["sentence", "token"]) \
    .setOutputCol("pos")

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

data = spark.createDataFrame([["ስካርቻ nlp እወዳለሁ"]]).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 = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic","am") 
    .setInputCols(Array("sentence", "token")) 
    .setOutputCol("pos")

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

val data = Seq("ስካርቻ nlp እወዳለሁ").toDF("text")

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

Model Information

Model Name: xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic
Compatibility: Spark NLP 3.4.2+
License: Open Source
Edition: Official
Input Labels: [document, token]
Output Labels: [ner]
Language: am
Size: 773.0 MB
Case sensitive: true
Max sentence length: 128

References

  • https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-ner-amharic
  • https://arxiv.org/abs/2103.11811
  • https://github.com/Michael-Beukman/NERTransfer
  • https://www.apache.org/licenses/LICENSE-2.0
  • https://github.com/Michael-Beukman/NERTransfer
  • h