Triple
T20125691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fentanyl |
E490748
|
entity |
| Predicate | medicalUse |
P40313
|
FINISHED |
| Object | anesthesia adjunct |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: anesthesia adjunct | Statement: [Fentanyl, medicalUse, anesthesia adjunct]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: medicalUse Context triple: [Fentanyl, medicalUse, anesthesia adjunct]
-
A.
medicinalUse
chosen
Indicates that one entity is used as a treatment or remedy for a disease, condition, or health-related purpose affecting another entity.
-
B.
medicalBackground
Indicates that an entity has a history of prior medical conditions, treatments, or health-related experiences relevant to its current state or context.
-
C.
usesMedicalKnowledge
Indicates that an entity applies or relies on medical knowledge in performing an action or making a decision.
-
D.
medicalAbuseOf
Indicates that one entity subjects another to harmful, exploitative, or unethical treatment within a medical or healthcare context.
-
E.
potentialTherapeuticUse
Indicates that something is being considered or investigated as a possible treatment or therapy for a condition or disease.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6674223008190827c454fe7ac86f4 |
completed | April 20, 2026, 5:49 p.m. |
| PD | Predicate disambiguation | batch_69e54cfb0d0081908e789b9b57e96668 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:31 p.m.