Arabic Named Entity Recognition (Modern Standard Arabic-MSA)

Description

Pretrained Named Entity Recognition model, uploaded to Hugging Face, adapted and imported into Spark NLP. bert-base-arabic-camelbert-msa-ner is a Arabic model orginally trained by CAMeL-Lab.

Predicted Entities

ORG, LOC, PERS, MISC

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_ner_bert_base_arabic_camelbert_msa_ner","ar") \
.setInputCols(["sentence", "token"]) \
.setOutputCol("ner")

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

data = spark.createDataFrame([["أنا أحب الشرارة NLP"]]).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_ner_bert_base_arabic_camelbert_msa_ner","ar") 
.setInputCols(Array("sentence", "token")) 
.setOutputCol("ner")

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

val data = Seq("أنا أحب الشرارة NLP").toDF("text")

val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("ar.ner.arabic_camelbert_msa_ner").predict("""أنا أحب الشرارة NLP""")

Model Information

Model Name: bert_ner_bert_base_arabic_camelbert_msa_ner
Compatibility: Spark NLP 3.4.2+
License: Open Source
Edition: Official
Input Labels: [document, token]
Output Labels: [ner]
Language: ar
Size: 407.1 MB
Case sensitive: true
Max sentence length: 128

References

  • https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa-ner
  • https://camel.abudhabi.nyu.edu/anercorp/
  • https://arxiv.org/abs/2103.06678
  • https://github.com/CAMeL-Lab/CAMeLBERT
  • https://github.com/CAMeL-Lab/camel_tools
  • https://github.com/CAMeL-Lab/camel_tools