Description
This pretrained pipeline is built on the top of bert_token_classifier_ner_linnaeus_species model.
Predicted Entities
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("bert_token_classifier_ner_linnaeus_species_pipeline", "en", "clinical/models")
text = '''First identified in chicken, vigilin homologues have now been found in human (6), Xenopus laevis (7), Drosophila melanogaster (8) and Schizosaccharomyces pombe.'''
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("bert_token_classifier_ner_linnaeus_species_pipeline", "en", "clinical/models")
val text = "First identified in chicken, vigilin homologues have now been found in human (6), Xenopus laevis (7), Drosophila melanogaster (8) and Schizosaccharomyces pombe."
val result = pipeline.fullAnnotate(text)
Results
| | ner_chunk | begin | end | ner_label | confidence |
|---:|:--------------------------|--------:|------:|:------------|-------------:|
| 0 | chicken | 20 | 26 | SPECIES | 0.998697 |
| 1 | human | 71 | 75 | SPECIES | 0.999767 |
| 2 | Xenopus laevis | 82 | 95 | SPECIES | 0.999918 |
| 3 | Drosophila melanogaster | 102 | 124 | SPECIES | 0.999925 |
| 4 | Schizosaccharomyces pombe | 134 | 158 | SPECIES | 0.999881 |
Model Information
| Model Name: | bert_token_classifier_ner_linnaeus_species_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.4.4+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 404.8 MB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- MedicalBertForTokenClassifier
- NerConverterInternalModel