Triple
T23513739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Direct Unsubsidized Loan |
E572500
|
entity |
| Predicate | interestRateVariesBy |
P98150
|
FINISHED |
| Object | academic level |
—
|
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: academic level | Statement: [Direct Unsubsidized Loan, interestRateVariesBy, academic level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interestRateVariesBy Context triple: [Direct Unsubsidized Loan, interestRateVariesBy, academic level]
-
A.
interestRateDetermination
Indicates the relationship by which the applicable interest rate is set, defined, or adjusted for a financial obligation or instrument.
-
B.
creditPolicyVariesBy
Indicates that the terms or rules of a credit policy differ depending on a specified factor, such as customer, product, region, or time period.
-
C.
interestRatePolicy
Indicates the relationship in which a governing financial authority sets or adjusts interest rates to influence economic conditions and borrowing costs.
-
D.
rateVariesBy
chosen
Indicates that the rate of something changes depending on a specified factor, condition, or category.
-
E.
interestRateName
Indicates the specific label or designation used to identify a particular interest rate.
- 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_69e245b5e4208190bac8a6509867e394 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1aa80174c819088c9c19fdcf2a133 |
completed | April 29, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_69f0621165c08190a0b27b1319733959 |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 6:08 p.m.