Triple
T1205059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Direct Student Loan Program |
E25868
|
entity |
| Predicate | loanDisbursement |
P9378
|
FINISHED |
| Object | funds sent to schools for students |
—
|
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: funds sent to schools for students | Statement: [Federal Direct Student Loan Program, loanDisbursement, funds sent to schools for students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loanDisbursement Context triple: [Federal Direct Student Loan Program, loanDisbursement, funds sent to schools for students]
-
A.
disbursementOption
chosen
Indicates the method or arrangement by which funds are paid out or distributed.
-
B.
loanType
Indicates the specific category or kind of loan associated with an entity or transaction.
-
C.
carriesMonetaryGrant
Indicates that one entity provides or includes a monetary grant for another entity or purpose.
-
D.
hasMonetaryGrant
Indicates that an entity provides or receives a monetary grant from another entity.
-
E.
dischargeRank
Indicates the rank or status an individual held at the time they were discharged from a role, service, or organization.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bdc0f8d08190b340012a9eb26275 |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5ed2b88190aab992913957e1cf |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.