Triple
T13777626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RIAA Multi-Platinum |
E331049
|
entity |
| Predicate | minimumUnits |
P19248
|
FINISHED |
| Object | 2000000 units |
—
|
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: 2000000 units | Statement: [RIAA Multi-Platinum, minimumUnits, 2000000 units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minimumUnits Context triple: [RIAA Multi-Platinum, minimumUnits, 2000000 units]
-
A.
minimumUnitSize
Indicates that there is a smallest allowable or defined size or quantity for the unit involved in the relationship.
-
B.
minorUnitsPerUnit
Indicates the number of smaller sub-units that collectively make up one whole unit in a given measurement or currency system.
-
C.
numberOfUnits
chosen
Indicates the quantity or count of discrete units associated with an entity or relationship.
-
D.
minorUnitUsage
Indicates how a minor or subordinate unit is used or functions in relation to a larger or primary unit.
-
E.
minimumGrant
Indicates that there is a lowest allowable or required amount of a grant associated with an entity or agreement.
- 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0239cbfc81909064ac2457fdfff5 |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbbe97846c819093b00ea117b64e0d |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 10:10 p.m.