Triple
T23513788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Perkins Loan |
E572501
|
entity |
| Predicate | maximumAnnualAmountUndergraduate |
P32143
|
FINISHED |
| Object | $5,500 |
—
|
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: $5,500 | Statement: [Federal Perkins Loan, maximumAnnualAmountUndergraduate, $5,500]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumAnnualAmountUndergraduate Context triple: [Federal Perkins Loan, maximumAnnualAmountUndergraduate, $5,500]
-
A.
maximumGrantAmount
Indicates the highest monetary value that can be awarded or granted under a specific grant, program, or agreement.
-
B.
undergraduateEnrollment
Indicates the number of undergraduate students enrolled in an institution or program.
-
C.
scholarshipLimitRelativeToFBS
Indicates a relationship where a scholarship limit is defined or constrained in comparison to the scholarship limits used in the Football Bowl Subdivision (FBS).
-
D.
maximumLoanAmountUSD
chosen
Indicates the highest amount of money, expressed in U.S. dollars, that can be loaned under a given agreement or condition.
-
E.
isPrimaryUndergraduateCollegeFor
Indicates that one institution serves as the main undergraduate college or school for a given entity (such as a university or student population).
- 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.