Triple
T7298324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cocaine |
E167778
|
entity |
| Predicate | hasMedicalUse |
P40313
|
FINISHED |
| Object | local anesthetic in some eye, ear, nose, and throat procedures |
—
|
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: local anesthetic in some eye, ear, nose, and throat procedures | Statement: [Cocaine, hasMedicalUse, local anesthetic in some eye, ear, nose, and throat procedures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMedicalUse Context triple: [Cocaine, hasMedicalUse, local anesthetic in some eye, ear, nose, and throat procedures]
-
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.
potentialTherapeuticUse
Indicates that something is being considered or investigated as a possible treatment or therapy for a condition or disease.
-
C.
hasPharmacologicalEffect
Indicates that one entity produces a specific pharmacological effect or action on another entity.
-
D.
usesDrug
Indicates that an entity consumes, administers, or otherwise makes use of a specified drug.
-
E.
hasDrug
Indicates that an entity possesses, is treated with, or is associated with a particular drug.
- 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_69c6888c820881909fc68f689fe1c251 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6eb8f83c881909e8eae85410f9659 |
completed | March 27, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69c6e76e67d88190bd3ca6864f45845a |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3 p.m.