Triple
T8019590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silverado Savings and Loan |
E186704
|
entity |
| Predicate | estimatedCostToTaxpayers |
P8361
|
FINISHED |
| Object | over 1 billion U.S. dollars |
—
|
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 1 billion U.S. dollars | Statement: [Silverado Savings and Loan, estimatedCostToTaxpayers, over 1 billion U.S. dollars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedCostToTaxpayers Context triple: [Silverado Savings and Loan, estimatedCostToTaxpayers, over 1 billion U.S. dollars]
-
A.
estimatedCost
Indicates the predicted or calculated monetary amount expected to be required for something, such as a project, item, or action.
-
B.
costToUser
Indicates the amount of cost or expense that is borne by, charged to, or incurred by the user.
-
C.
economicDamageApprox
Indicates that one entity has caused or is associated with an estimated or approximate amount of economic damage to another entity or system.
-
D.
budgetaryEffect
chosen
Indicates the financial impact or change in budget resulting from a particular action, decision, or policy.
-
E.
programCost
Indicates the monetary or resource expenditure required to implement, run, or participate in a particular program.
- 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_69ca82ac7fc081909b1398cf025423af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3e8bc90081909f6f5878e6f1f241 |
completed | March 31, 2026, 3:24 a.m. |
| PD | Predicate disambiguation | batch_69cb049253d08190bafcecfde493ab8b |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:20 p.m.