Triple
T1205061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Direct Student Loan Program |
E25868
|
entity |
| Predicate | hasBorrowerType |
P379
|
FINISHED |
| Object | student borrower |
—
|
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: student borrower | Statement: [Federal Direct Student Loan Program, hasBorrowerType, student borrower]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBorrowerType Context triple: [Federal Direct Student Loan Program, hasBorrowerType, student borrower]
-
A.
eligibleBorrower
Indicates that an entity meets the required conditions to be allowed to borrow (e.g., money, items, or resources) under a given set of rules or policies.
-
B.
hasTypeOfRecipient
chosen
Indicates that an entity is associated with a specific category or kind of recipient it is intended for or directed to.
-
C.
hasBorrowingsFrom
Indicates that one entity has taken, adopted, or derived elements (such as features, ideas, or content) from another entity.
-
D.
lenderType
Indicates the classification or category of the lender involved in a lending relationship (e.g., bank, individual, institution).
-
E.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
- 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.