Triple
T23513791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Perkins Loan |
E572501
|
entity |
| Predicate | maximumAggregateAmountGraduate |
P32143
|
FINISHED |
| Object | $60,000 including undergraduate Perkins |
—
|
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: $60,000 including undergraduate Perkins | Statement: [Federal Perkins Loan, maximumAggregateAmountGraduate, $60,000 including undergraduate Perkins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumAggregateAmountGraduate Context triple: [Federal Perkins Loan, maximumAggregateAmountGraduate, $60,000 including undergraduate Perkins]
-
A.
maximumGrantAmount
Indicates the highest monetary value that can be awarded or granted under a specific grant, program, or agreement.
-
B.
maximumLoanAmountUSD
chosen
Indicates the highest amount of money, expressed in U.S. dollars, that can be loaned under a given agreement or condition.
-
C.
hasMaximumGrade
Indicates that an entity possesses the highest possible grade or score within a defined grading or evaluation system.
-
D.
maximumRebateAmount
Indicates the highest rebate value that can be granted or applied in a given context.
-
E.
maximumEngineeringScholarshipValueCAD
Indicates the highest monetary amount, in Canadian dollars, that can be awarded for an engineering scholarship.
- 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.