Triple
T2348964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glass–Owen Act |
E47399
|
entity |
| Predicate | createdNumberOfRegionalBanks |
P5391
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Glass–Owen Act, createdNumberOfRegionalBanks, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: createdNumberOfRegionalBanks Context triple: [Glass–Owen Act, createdNumberOfRegionalBanks, 12]
-
A.
numberOfFederalReserveBanks
chosen
Indicates the quantity of Federal Reserve Banks associated with or relevant to a given entity.
-
B.
numberOfRegions
Indicates the total count of distinct regions associated with or contained within a given entity.
-
C.
numberOfTargetInstitutions
Indicates the count of institutions that are designated or identified as targets in a given context or dataset.
-
D.
numberOfRegionalCouncils
Indicates the total count of regional councils associated with a given entity.
-
E.
branchCount
Indicates the number of branches associated with a given entity or structure.
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abcb802da08190980100444010f91e |
completed | March 7, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69abc5981ce48190a3f7852d28276e11 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:54 p.m.