Triple
T5364324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howard G. Buffett Foundation |
E103092
|
entity |
| Predicate | grantRecipientType |
P22506
|
FINISHED |
| Object | non-governmental organizations |
—
|
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: non-governmental organizations | Statement: [Howard G. Buffett Foundation, grantRecipientType, non-governmental organizations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grantRecipientType Context triple: [Howard G. Buffett Foundation, grantRecipientType, non-governmental organizations]
-
A.
typeOfGrant
Indicates the specific category or kind of grant associated with an entity.
-
B.
grantType
Indicates the specific authorization or credential flow used to obtain access or permissions in a grant-based process.
-
C.
beneficiaryType
chosen
Indicates the type or category of beneficiary that receives or is intended to receive the benefit or outcome of an action or resource.
-
D.
granteeRecognition
Indicates that an entity acknowledges, credits, or formally recognizes a grantee for their role, contribution, or status in relation to a grant.
-
E.
grantmakingType
Indicates the specific category or method by which grants are awarded or administered in a grantmaking relationship.
- 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_69bd43daa3e4819090b59d127db70e57 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd865d42508190a1a96121674c1020 |
completed | March 20, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69bd845f41f88190b75b8b64b9e41862 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:02 p.m.