Triple
T19157384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zetia |
E468959
|
entity |
| Predicate | hasTypicalDose |
P130936
|
FINISHED |
| Object | 10 mg once daily |
—
|
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: 10 mg once daily | Statement: [Zetia, hasTypicalDose, 10 mg once daily]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalDose Context triple: [Zetia, hasTypicalDose, 10 mg once daily]
-
A.
hasDefinedDailyDose
Indicates that an entity has an established standard amount intended to be taken or used per day.
-
B.
dosageLevel
chosen
Indicates the specific amount or intensity of a substance or treatment administered in a given dose.
-
C.
hasDoseUnit
Indicates the unit of measurement in which a specified dose or quantity of a substance is expressed.
-
D.
hasInitialDose
Indicates that an entity has received or is assigned a first or starting dose of a treatment, medication, or substance.
-
E.
hasMaintenanceDose
Indicates that an entity is associated with a specific ongoing dose used to maintain a desired therapeutic effect after initial treatment.
- 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_69d8dd084ff48190ac0f8c46ee722629 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5eeba91a081909c04d61d6117da06 |
completed | April 20, 2026, 9:15 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b83d6881908e6271c620f74100 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:06 p.m.