Description
Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. ner-bert-german is a German model originally trained by mschiesser.
Predicted Entities
LOC, ORG, PER
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
tokenClassifier = BertForTokenClassification.pretrained("bert_token_classifier_ner_german","de") \
.setInputCols(["document", "token"]) \
.setOutputCol("ner")
pipeline = Pipeline(stages=[documentAssembler, tokenizer, tokenClassifier])
data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
result = pipeline.fit(data).transform(data)
Model Information
| Model Name: | bert_token_classifier_ner_german |
| Compatibility: | Spark NLP 5.5.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [document, token] |
| Output Labels: | [ner] |
| Language: | de |
| Size: | 665.1 MB |
References
References
- https://huggingface.co/mschiesser/ner-bert-german
- https://en.wikipedia.org/wiki/Named-entity_recognition