Named Entity Recognition Components
We provide several Named Entity Recognition (NER) components. Named Entity Recognition is the task of identifying short relevant spans of text, named entities, and classifying them into pre-defined categories. In the case of clinical documents, these entities can be scores, disorders, behaviors, codes, dates, quantities, etc.
Span setters: where are stored extracted entities ?
A component assigns entities to a document by adding them to the doc.ents or doc.spans[group] attributes. doc.ents only supports non overlapping entities, therefore, if two entities overlap, the longest one will be kept. doc.spans[group] on the other hand, can contain overlapping entities. To control where entities are added, you can use the span_setter argument in any of these component.
Valid values for the span_setter argument of a component can be :
- a (doc, matches) -> None callable
- a span group name
- a list of span group names
- a dict of group name to True or list of labels
The group name "ents" is a special case, and will add the matches to doc.ents
Examples
span_setter=["ents", "ckd"]will add the matches to bothdoc.entsanddoc.spans["ckd"]. It is equivalent to{"ents": True, "ckd": True}.span_setter={"ents": ["foo", "bar"]}will add the matches with label "foo" and "bar" todoc.ents.span_setter="ents"will add all matches only todoc.ents.span_setter="ckd"will add all matches only todoc.spans["ckd"].
Available components
| Component | Description |
|---|---|
eds.covid | A COVID mentions detector |
eds.charlson | A Charlson score extractor |
eds.sofa | A SOFA score extractor |
eds.elston_ellis | An Elston & Ellis code extractor |
eds.emergency_priority | A priority score extractor |
eds.emergency_ccmu | A CCMU score extractor |
eds.emergency_gemsa | A GEMSA score extractor |
eds.tnm | A TNM score extractor |
eds.adicap | A ADICAP codes extractor |
eds.drugs | A drug mentions extractor |
eds.cim10 | A CIM10 terminology matcher |
eds.umls | An UMLS terminology matcher |
eds.ckd | CKD extractor |
eds.copd | COPD extractor |
eds.cerebrovascular_accident | Cerebrovascular accident extractor |
eds.congestive_heart_failure | Congestive heart failure extractor |
eds.connective_tissue_disease | Connective tissue disease extractor |
eds.dementia | Dementia extractor |
eds.diabetes | Diabetes extractor |
eds.hemiplegia | Hemiplegia extractor |
eds.leukemia | Leukemia extractor |
eds.liver_disease | Liver disease extractor |
eds.lymphoma | Lymphoma extractor |
eds.myocardial_infarction | Myocardial infarction extractor |
eds.peptic_ulcer_disease | Peptic ulcer disease extractor |
eds.peripheral_vascular_disease | Peripheral vascular disease extractor |
eds.solid_tumor | Solid tumor extractor |
eds.alcohol | Alcohol consumption extractor |
eds.tobacco | Tobacco consumption extractor |