Triple
T7113758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bezos Earth Fund |
E165765
|
entity |
| Predicate | typeOfGrantmaker |
P12398
|
FINISHED |
| Object | private foundation |
—
|
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: private foundation | Statement: [Bezos Earth Fund, typeOfGrantmaker, private foundation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfGrantmaker Context triple: [Bezos Earth Fund, typeOfGrantmaker, private foundation]
-
A.
grantmakingType
chosen
Indicates the specific category or method by which grants are awarded or administered in a grantmaking relationship.
-
B.
funderType
Indicates the category or kind of organization or individual that provides funding in the relationship.
-
C.
nonprofitType
Indicates the specific category or classification of a nonprofit organization based on its legal or functional type.
-
D.
funderOf
Indicates that one entity provides financial support or funding for another entity, project, or activity.
-
E.
typeOfPatronage
Indicates the specific kind or category of support, sponsorship, or backing that one entity provides to another.
- 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_69c6888120f081908f8f01b201dc4a4c |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e5ef813c8190bec0ab0cbae430e5 |
completed | March 27, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c4f9788190830288d00cc37026 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:43 p.m.