Triple
T10978310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FDIC insurance limit |
E259429
|
entity |
| Predicate | previousStandardAmount |
P96424
|
FINISHED |
| Object | 100000 USD |
—
|
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: 100000 USD | Statement: [FDIC insurance limit, previousStandardAmount, 100000 USD]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousStandardAmount Context triple: [FDIC insurance limit, previousStandardAmount, 100000 USD]
-
A.
previousDenomination
Indicates that one entity was the earlier or former denomination (name, value, or classification) of another entity in a sequence of denominations.
-
B.
previousCurrency
Indicates that one currency served as the predecessor or was replaced by another currency in a monetary system or sequence.
-
C.
approximateNumberAwarded
Indicates the estimated quantity of awards or recognitions given in a particular context or event.
-
D.
originalPrice
Indicates the monetary amount that something initially cost before any discounts, changes, or adjustments were applied.
-
E.
spendSize
Indicates the amount or magnitude of spending associated with an entity or transaction.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d771f6a9448190b3932ee801ae0da9 |
completed | April 9, 2026, 9:31 a.m. |
| PD | Predicate disambiguation | batch_69d72e9055908190b438f039574aaaaf |
completed | April 9, 2026, 4:44 a.m. |
| PDg | Predicate description generation | batch_69d732242fdc8190be77d1f730a42935 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:24 p.m.