| """Simple UMLS linker using SciSpacy.""" | |
| import spacy | |
| from scispacy.linking import UmlsEntityLinker | |
| nlp = spacy.load("en_core_sci_lg") | |
| linker = UmlsEntityLinker(resolve_abbreviations=True, disambiguate=True) | |
| nlp.add_pipe(linker) | |
| def link_umls(text: str): | |
| doc = nlp(text) | |
| results = [] | |
| for ent in doc.ents: | |
| for cui, score in ent._.kb_ents: | |
| results.append( | |
| {"text": ent.text, "cui": cui, "score": score} | |
| ) | |
| break # take top candidate | |
| return results | |