Description
This pretrained pipeline is built on the top of ner_anatomy_coarse model.
How to use
pipeline = PretrainedPipeline("ner_anatomy_coarse_pipeline", "en", "clinical/models")
pipeline.annotate("content in the lung tissue")
val pipeline = new PretrainedPipeline("ner_anatomy_coarse_pipeline", "en", "clinical/models")
pipeline.annotate("content in the lung tissue")
import nlu
nlu.load("en.med_ner.anatomy_coarse.pipeline").predict("""content in the lung tissue""")
Results
| | ner_chunk | entity |
|---:|------------------:|----------:|
| 0 | lung tissue | Anatomy |
Model Information
| Model Name: | ner_anatomy_coarse_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 3.4.1+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.7 GB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverter