Triple
T11919469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Reserve Bank of Atlanta |
E283616
|
entity |
| Predicate | numberOfRegionalReserveBanks |
P102357
|
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: [Federal Reserve Bank of Atlanta, numberOfRegionalReserveBanks, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRegionalReserveBanks Context triple: [Federal Reserve Bank of Atlanta, numberOfRegionalReserveBanks, 12]
-
A.
numberOfFederalReserveBanks
Indicates the quantity of Federal Reserve Banks associated with or relevant to a given entity.
-
B.
numberOfBanks
Indicates the quantity or count of banks associated with a given entity or context.
-
C.
centralBank
Indicates that an entity functions as the primary monetary authority responsible for issuing currency and implementing monetary policy for a specific jurisdiction.
-
D.
numberOfFederalLandBanksCreated
Indicates the total count of federal land banks that were established or created in a given context.
-
E.
federalReserveDistrictNumber
Indicates the specific Federal Reserve district number with which an entity (such as a bank or location) is associated.
- 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_69d6ab2c07e88190ba13b0d21fd6cf33 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e8dff77481908cacf6ad03df34ac |
completed | April 10, 2026, 12:11 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3632ac8190b13e53c2b5db7125 |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8dd0ba0f88190b7d5e358c27ca184 |
completed | April 10, 2026, 11:20 a.m. |
Created at: April 8, 2026, 9:44 p.m.