Triple
T6777992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Land Banks |
E155606
|
entity |
| Predicate | maximumLoanTerm |
P10122
|
FINISHED |
| Object | long-term amortized loans |
—
|
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: long-term amortized loans | Statement: [Federal Land Banks, maximumLoanTerm, long-term amortized loans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumLoanTerm Context triple: [Federal Land Banks, maximumLoanTerm, long-term amortized loans]
-
A.
hasLongerRepaymentTermThan
Indicates that the repayment term of one entity (e.g., a loan or debt) is longer in duration than the repayment term of another entity.
-
B.
maximumBondMaturity
Indicates the longest allowable or actual time period until a bond tied to an entity reaches its maturity date.
-
C.
timeHorizonOfLoans
chosen
Indicates the length of time over which loans are scheduled to be outstanding or repaid.
-
D.
maximumAccrualPeriod
Indicates the longest time span over which something (such as interest, benefits, or rights) can accumulate before it stops accruing.
-
E.
maximumLoanAmountUSD
Indicates the highest amount of money, expressed in U.S. dollars, that can be loaned under a given agreement or condition.
- 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_69c688162bf8819088b664b5c3b5be7a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2689d408190bc2c1ce4ae9c1b13 |
completed | March 27, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69c6d095dcac8190bb9b943f50a7f885 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:13 p.m.