Triple
T7526066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Series I savings bonds |
E177894
|
entity |
| Predicate | electronicPurchaseLimitPerPersonPerYear |
P77220
|
FINISHED |
| Object | 10000 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: 10000 USD | Statement: [Series I savings bonds, electronicPurchaseLimitPerPersonPerYear, 10000 USD]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: electronicPurchaseLimitPerPersonPerYear Context triple: [Series I savings bonds, electronicPurchaseLimitPerPersonPerYear, 10000 USD]
-
A.
maximumAnnualPurchaseLimitPerSSN
chosen
Indicates the highest total amount that may be purchased within a year by any single individual, as identified by their Social Security Number.
-
B.
requiredMonthlySilverPurchaseMaximum
Indicates the maximum amount of silver that must be purchased each month under a given requirement or agreement.
-
C.
statutoryLimitPerIncidentUSD
Indicates the maximum monetary amount, in U.S. dollars, that is legally allowed to be claimed or paid for a single incident under a specific statute or regulation.
-
D.
minimumSessionsPerYear
Indicates the smallest number of sessions that must occur within a one-year period.
-
E.
annualQuotaNumber
Indicates the specific numeric value assigned as an entity’s quota for a given year.
- 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_69c69f29bf3081909a146aec7755f185 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f7c7ac5c8190bbf9befdff791de0 |
completed | March 27, 2026, 9:33 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d6bb808190bdd04499fd3bceb6 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:46 p.m.