Triple
T4259059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berea College |
E96056
|
entity |
| Predicate | endowmentModel |
P59
|
FINISHED |
| Object | relies on endowment and donations to cover tuition |
—
|
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: relies on endowment and donations to cover tuition | Statement: [Berea College, endowmentModel, relies on endowment and donations to cover tuition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: endowmentModel Context triple: [Berea College, endowmentModel, relies on endowment and donations to cover tuition]
-
A.
endowment
Indicates that a resource, asset, or benefit is provided or allocated to an entity, typically as a lasting or dedicated funding source.
-
B.
endowmentCurrency
Indicates the type of currency in which an endowment is denominated or valued.
-
C.
fundingModel
chosen
Indicates how an entity is financially supported or sustained, such as through specific revenue sources, payment structures, or funding mechanisms.
-
D.
hasEndowmentType
Indicates that an entity is associated with a particular category or type of endowment.
-
E.
funderOf
Indicates that one entity provides financial support or funding for another entity, project, or activity.
- 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_69b3454095ac81909c2494f7ff294af1 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34f7ec4508190a5067f1112ac7dca |
completed | March 12, 2026, 11:42 p.m. |
| PD | Predicate disambiguation | batch_69b347f73e008190a908a48ef389945a |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:06 p.m.