Description
This pretrained pipeline is built on the top of bert_token_classifier_ner_jnlpba_cellular model.
Predicted Entities
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("bert_token_classifier_ner_jnlpba_cellular_pipeline", "en", "clinical/models")
text = '''The results suggest that activation of protein kinase C, but not new protein synthesis, is required for IL-2 induction of IFN-gamma and GM-CSF cytoplasmic mRNA. It also was observed that suppression of cytokine gene expression by these agents was independent of the inhibition of proliferation. These data indicate that IL-2 and IL-12 may have distinct signaling pathways leading to the induction of IFN-gammaand GM-CSFgene expression, andthatthe NK3.3 cell line may serve as a novel model for dissecting the biochemical and molecular events involved in these pathways. A functional T-cell receptor signaling pathway is required for p95vav activity. Stimulation of the T-cell antigen receptor ( TCR ) induces activation of multiple tyrosine kinases, resulting in phosphorylation of numerous intracellular substrates. One substrate is p95vav, which is expressed exclusively in hematopoietic and trophoblast cells..'''
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("bert_token_classifier_ner_jnlpba_cellular_pipeline", "en", "clinical/models")
val text = "The results suggest that activation of protein kinase C, but not new protein synthesis, is required for IL-2 induction of IFN-gamma and GM-CSF cytoplasmic mRNA. It also was observed that suppression of cytokine gene expression by these agents was independent of the inhibition of proliferation. These data indicate that IL-2 and IL-12 may have distinct signaling pathways leading to the induction of IFN-gammaand GM-CSFgene expression, andthatthe NK3.3 cell line may serve as a novel model for dissecting the biochemical and molecular events involved in these pathways. A functional T-cell receptor signaling pathway is required for p95vav activity. Stimulation of the T-cell antigen receptor ( TCR ) induces activation of multiple tyrosine kinases, resulting in phosphorylation of numerous intracellular substrates. One substrate is p95vav, which is expressed exclusively in hematopoietic and trophoblast cells.."
val result = pipeline.fullAnnotate(text)
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("bert_token_classifier_ner_jnlpba_cellular_pipeline", "en", "clinical/models")
text = '''The results suggest that activation of protein kinase C, but not new protein synthesis, is required for IL-2 induction of IFN-gamma and GM-CSF cytoplasmic mRNA. It also was observed that suppression of cytokine gene expression by these agents was independent of the inhibition of proliferation. These data indicate that IL-2 and IL-12 may have distinct signaling pathways leading to the induction of IFN-gammaand GM-CSFgene expression, andthatthe NK3.3 cell line may serve as a novel model for dissecting the biochemical and molecular events involved in these pathways. A functional T-cell receptor signaling pathway is required for p95vav activity. Stimulation of the T-cell antigen receptor ( TCR ) induces activation of multiple tyrosine kinases, resulting in phosphorylation of numerous intracellular substrates. One substrate is p95vav, which is expressed exclusively in hematopoietic and trophoblast cells..'''
result = pipeline.fullAnnotate(text)
Results
| | ner_chunk | begin | end | ner_label | confidence |
|---:|:--------------------------------------|--------:|------:|:------------|-------------:|
| 0 | protein kinase C | 39 | 54 | protein | 0.993263 |
| 1 | IL-2 | 104 | 107 | protein | 0.969095 |
| 2 | IFN-gamma and GM-CSF cytoplasmic mRNA | 122 | 158 | RNA | 0.998495 |
| 3 | cytokine gene | 202 | 214 | DNA | 0.953537 |
| 4 | IL-2 | 320 | 323 | protein | 0.999317 |
| 5 | IL-12 | 329 | 333 | protein | 0.999216 |
| 6 | IFN-gammaand GM-CSFgene | 400 | 422 | protein | 0.995236 |
| 7 | NK3.3 cell line | 447 | 461 | cell_line | 0.998958 |
| 8 | T-cell receptor | 583 | 597 | protein | 0.987655 |
| 9 | p95vav | 633 | 638 | protein | 0.999857 |
| 10 | T-cell antigen receptor | 669 | 691 | protein | 0.99891 |
| 11 | TCR | 695 | 697 | protein | 0.998049 |
| 12 | tyrosine kinases | 732 | 747 | protein | 0.999636 |
| 13 | p95vav | 834 | 839 | protein | 0.999842 |
| 14 | hematopoietic and trophoblast cells | 876 | 910 | cell_type | 0.999709 |
Model Information
| Model Name: | bert_token_classifier_ner_jnlpba_cellular_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