Triple
T22690667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vitrakvi |
E561039
|
entity |
| Predicate | hasPediatricUse |
P149284
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Vitrakvi, hasPediatricUse, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPediatricUse Context triple: [Vitrakvi, hasPediatricUse, yes]
-
A.
mayBeUsedOffLabelFor
Indicates that something (typically a drug or treatment) can be used for a purpose or condition other than its officially approved or intended use.
-
B.
hasRetailUse
Indicates that an entity is used, intended, or designated for retail activities such as selling goods or services directly to consumers.
-
C.
hasEmergencyUse
Indicates that an entity is authorized, designated, or configured for use specifically in emergency situations or conditions.
-
D.
hasEmergencyUseBy
Indicates that something is authorized for emergency use until a specified date or time.
-
E.
hasHumanUse
Indicates that something is used, employed, or utilized by humans for a particular purpose or benefit.
- F. None of above. chosen
Provenance (4 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_69e2454d71b48190a1f80af9f82b6fcf |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1789a1fd08190bce5fa0babe695d3 |
completed | April 29, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69ee62b2259c819091ed1387a748b9f3 |
completed | April 26, 2026, 7:08 p.m. |
| PDg | Predicate description generation | batch_69ee8843d3308190b6e22bb98ae5c3d8 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 3:13 p.m.