Leyli
Biomedical knowledge engine demo
Leyli Biomedical Knowledge Engine Demo
Turn biomedical documents into knowledge graphs, GraphRAG context, and source-traceable AI evidence.
Extraction Models
Choose biomedical NER and relation extraction settings.
GLiNER detects many biomedical entity types with configurable labels.
Enhanced hybrid combines biomedical patterns, sentence evidence, and ontology validation.
Ontologies
Select ontology sources for concept linking and surgical knowledge grounding. UMLS and SNOMED CT are active today; the other surgery ontologies are included as local-ready slots for the next loaders.
Input Sources
Select one or more places your documents come from. Add as many sources as needed.
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Document Content
Use direct upload, file sources, folder sources, or pasted text.
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Ready to build the knowledge graph?
Use the files, sources, and text above to extract entities, relations, ontology links, and GraphRAG evidence.