Description
This pretrained pipeline is built on the top of ner_bionlp_biobert model.
Predicted Entities
Gene_or_gene_product, Cancer, Cell, Cellular_component, Organism, Multi-tissue_structure, Developing_anatomical_structure, Amino_acid, Organ, Anatomical_system, Tissue, Organism_subdivision, Simple_chemical, Organism_substance, Immaterial_anatomical_entity, Pathological_formation
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("ner_bionlp_biobert_pipeline", "en", "clinical/models")
text = '''Both the erbA IRES and the erbA/myb virus constructs transformed erythroid cells after infection of bone marrow or blastoderm cultures. The erbA/myb IRES virus exhibited a 5-10-fold higher transformed colony forming efficiency than the erbA IRES virus in the blastoderm assay'''
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("ner_bionlp_biobert_pipeline", "en", "clinical/models")
val text = "Both the erbA IRES and the erbA/myb virus constructs transformed erythroid cells after infection of bone marrow or blastoderm cultures. The erbA/myb IRES virus exhibited a 5-10-fold higher transformed colony forming efficiency than the erbA IRES virus in the blastoderm assay"
val result = pipeline.fullAnnotate(text)
import nlu
nlu.load("en.med_ner.bionlp_biobert.pipeline").predict("""Both the erbA IRES and the erbA/myb virus constructs transformed erythroid cells after infection of bone marrow or blastoderm cultures. The erbA/myb IRES virus exhibited a 5-10-fold higher transformed colony forming efficiency than the erbA IRES virus in the blastoderm assay""")
Results
| | ner_chunk | begin | end | ner_label | confidence |
|---:|:--------------------|--------:|------:|:-----------------------|-------------:|
| 0 | erbA | 9 | 12 | Gene_or_gene_product | 1 |
| 1 | IRES | 14 | 17 | Organism | 0.754 |
| 2 | virus | 36 | 40 | Organism | 0.9999 |
| 3 | erythroid cells | 65 | 79 | Cell | 0.99855 |
| 4 | bone | 100 | 103 | Multi-tissue_structure | 0.9794 |
| 5 | marrow | 105 | 110 | Multi-tissue_structure | 0.9631 |
| 6 | blastoderm cultures | 115 | 133 | Cell | 0.9868 |
| 7 | IRES virus | 149 | 158 | Organism | 0.99985 |
| 8 | erbA | 236 | 239 | Gene_or_gene_product | 0.9977 |
| 9 | IRES virus | 241 | 250 | Organism | 0.9911 |
| 10 | blastoderm | 259 | 268 | Cell | 0.9941 |
Model Information
| Model Name: | ner_bionlp_biobert_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.4.4+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 422.2 MB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- BertEmbeddings
- MedicalNerModel
- NerConverterInternalModel