Triple
T849194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trump Foundation |
E18344
|
entity |
| Predicate | charityType |
P13548
|
FINISHED |
| Object | grantmaking 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: grantmaking foundation | Statement: [Trump Foundation, charityType, grantmaking foundation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: charityType Context triple: [Trump Foundation, charityType, grantmaking foundation]
-
A.
associatedCharity
Indicates that one entity has a formal or recognized charitable affiliation or partnership with another entity.
-
B.
nonprofitType
chosen
Indicates the specific category or classification of a nonprofit organization based on its legal or functional type.
-
C.
charityComponent
Indicates that one entity functions as a charitable element, feature, or part within another entity or larger arrangement.
-
D.
philanthropicInitiative
Indicates an action or relationship where an entity undertakes or supports activities intended to promote the welfare of others, typically through charitable or socially beneficial efforts.
-
E.
hasCharitySingle
Indicates that an entity is associated with exactly one specific charitable organization or charitable initiative.
- 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_69a4938b04208190b82e1df6b572c548 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac1fac3481909cba7070ce31a9b3 |
completed | March 1, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69a4aa807adc8190ad808a573cf8e923 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.