Triple
T23123066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PLUS Loan |
E576951
|
entity |
| Predicate | canBeDeniedForAdverseCredit |
P150993
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [PLUS Loan, canBeDeniedForAdverseCredit, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeDeniedForAdverseCredit Context triple: [PLUS Loan, canBeDeniedForAdverseCredit, true]
-
A.
hasCreditRating
Indicates that an entity is assigned a formal assessment of its creditworthiness, typically expressed as a credit score or rating.
-
B.
hasBureau
Indicates that an entity is associated with or possesses a specific bureau, such as an office, department, or administrative unit.
-
C.
hasAlternativeCredit
Indicates that an entity is associated with a different or substitute form of credit or credit option than the primary one.
-
D.
hasCredit
Indicates that an entity possesses or is assigned a credit, such as financial credit, academic credit, or acknowledgment for a contribution.
-
E.
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.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69ef9b7494f4819088ae59ea3d0ae8ab |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 17, 2026, 3:59 p.m.