Triple
T1808347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SCORE mentoring program |
E40271
|
entity |
| Predicate | legalStatusOfOperator |
P2250
|
FINISHED |
| Object | 501(c)(3) nonprofit organization |
—
|
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: 501(c)(3) nonprofit organization | Statement: [SCORE mentoring program, legalStatusOfOperator, 501(c)(3) nonprofit organization]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStatusOfOperator Context triple: [SCORE mentoring program, legalStatusOfOperator, 501(c)(3) nonprofit organization]
-
A.
regulationStatus
Indicates the regulatory condition or compliance state that applies to an entity under relevant rules or laws.
-
B.
hasLegalStatus
chosen
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
-
C.
hasOperatorJurisdiction
Indicates that a particular operator has official authority or control over a specified entity, area, or operation.
-
D.
operatingStatus
Indicates whether an entity is currently functioning, active, or in service versus inactive, closed, or out of service.
-
E.
airOperatorCertificateStatus
Indicates the current regulatory approval state of an air operator’s certificate authorizing it to conduct aviation operations.
- 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_69a88643a3388190a612f2ebe1fb29e7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab694d75ac8190a4d61399c04b9fb9 |
completed | March 6, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69aa61d6b8ec8190a1597b2e44ea6534 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.