Triple
T23123049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PLUS Loan |
E576951
|
entity |
| Predicate | maximumAmount |
P125398
|
FINISHED |
| Object | cost of attendance minus other financial aid |
—
|
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: cost of attendance minus other financial aid | Statement: [PLUS Loan, maximumAmount, cost of attendance minus other financial aid]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumAmount Context triple: [PLUS Loan, maximumAmount, cost of attendance minus other financial aid]
-
A.
maximumGrantAmount
Indicates the highest monetary value that can be awarded or granted under a specific grant, program, or agreement.
-
B.
maximumLoanAmountUSD
Indicates the highest amount of money, expressed in U.S. dollars, that can be loaned under a given agreement or condition.
-
C.
monetaryLimit
chosen
Indicates a constraint or maximum allowable amount of money associated with an action, transaction, or relationship.
-
D.
maximumRebateAmount
Indicates the highest rebate value that can be granted or applied in a given context.
-
E.
hasMaximumBalanceLimit
Indicates that there is an upper bound on the balance that an account or entity is allowed to hold.
- 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_69e245f6c2e881909a228fdcfeb7c7d3 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18e517a0481909829a73fdf255d1c |
completed | April 29, 2026, 4:51 a.m. |
| PD | Predicate disambiguation | batch_69ef89f020588190b43393e048e7eda3 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 3:59 p.m.