Triple
T1678522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Comic Relief |
E36285
|
entity |
| Predicate | type of nonprofit |
P13548
|
FINISHED |
| Object | grant-making charity |
—
|
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: grant-making charity | Statement: [Comic Relief, type of nonprofit, grant-making charity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: type of nonprofit Context triple: [Comic Relief, type of nonprofit, grant-making charity]
-
A.
nonprofitType
chosen
Indicates the specific category or classification of a nonprofit organization based on its legal or functional type.
-
B.
nonProfitContext
Indicates that the relationship or action occurs within, is associated with, or is specifically relevant to a nonprofit or charitable organizational context.
-
C.
genreOfPhilanthropy
Indicates the specific type or category of philanthropic activity to which an act, initiative, or organization belongs.
-
D.
grantmakingType
Indicates the specific category or method by which grants are awarded or administered in a grantmaking relationship.
-
E.
nonprofitStatus
Indicates that an entity operates as a nonprofit organization, typically meeting legal or regulatory criteria for nonprofit status.
- 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_69a886139ed081909af0940aa9313512 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aba644070c81908745b56d981fe273 |
completed | March 7, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69aa61b57a6881909373af287ef24799 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:29 p.m.