Description
This pipeline extracts mentions of anatomical sites from health-related text in colloquial language.
Predicted Entities
Live Demo Open in Colab Copy S3 URI
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("ner_vop_anatomy_pipeline", "en", "clinical/models")
pipeline.annotate("
Ugh, I pulled a muscle in my neck from sleeping weird last night. It's like a knot in my trapezius and it hurts to turn my head.
")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("ner_vop_anatomy_pipeline", "en", "clinical/models")
val result = pipeline.annotate("
Ugh, I pulled a muscle in my neck from sleeping weird last night. It's like a knot in my trapezius and it hurts to turn my head.
")
Results
| chunk | ner_label |
|:----------|:------------|
| muscle | BodyPart |
| neck | BodyPart |
| trapezius | BodyPart |
| head | BodyPart |
Model Information
| Model Name: | ner_vop_anatomy_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.4.4+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 791.6 MB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverter