Triple
T426152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gold Museum (Museo del Oro) |
E9611
|
entity |
| Predicate | goldObjectsCount |
P13765
|
FINISHED |
| Object | over 30,000 |
—
|
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: over 30,000 | Statement: [Gold Museum (Museo del Oro), goldObjectsCount, over 30,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: goldObjectsCount Context triple: [Gold Museum (Museo del Oro), goldObjectsCount, over 30,000]
-
A.
authorizedCoinMetal
Indicates that a particular metal is officially approved for use in minting a given coin.
-
B.
hasCrownCount
Indicates the number of crowns that an entity possesses or is associated with.
-
C.
numberOfIronPieces
Indicates the quantity or count of iron pieces associated with an entity.
-
D.
numberOfFiguresDepicted
Indicates the total count of distinct figures shown within a given depiction or representation.
-
E.
numberBuilt
Indicates the total count of items or structures that have been constructed or produced.
- 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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eed691c4819092b7e57306114bbc |
completed | Feb. 28, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69a2edd6736c81909a6ca549f77b4345 |
completed | Feb. 28, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69a2eeb93584819082f23eff13e17c4f |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.