Triple
T10978305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FDIC insurance limit |
E259429
|
entity |
| Predicate | hasStandardAmount |
P20937
|
FINISHED |
| Object | 250000 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: 250000 USD | Statement: [FDIC insurance limit, hasStandardAmount, 250000 USD]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStandardAmount Context triple: [FDIC insurance limit, hasStandardAmount, 250000 USD]
-
A.
hasMonetaryComponent
chosen
Indicates that something includes, involves, or is associated with a monetary or financial element.
-
B.
hasRateType
Indicates the specific category or scheme under which a rate (such as a price, fee, or interest) is defined or applied.
-
C.
hasStandardSeries
Indicates that an entity is associated with, or belongs to, a designated standard series or standardized sequence.
-
D.
hasServiceStandard
Indicates that an entity is associated with, or governed by, a defined service standard specifying expected service levels or quality.
-
E.
hasMinimumLoadAmount
Indicates that there is a specified lowest allowable or required amount of load that must be met or exceeded.
- 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_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. |
Created at: April 8, 2026, 9:24 p.m.