Triple
T2366466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | science and technology award foundation |
E47390
|
entity |
| Predicate | mayBeFundedBy |
P67
|
FINISHED |
| Object | endowments |
—
|
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: endowments | Statement: [science and technology award foundation, mayBeFundedBy, endowments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayBeFundedBy Context triple: [science and technology award foundation, mayBeFundedBy, endowments]
-
A.
fundedBy
chosen
Indicates that an entity receives financial support or resources from another entity.
-
B.
funderOf
Indicates that one entity provides financial support or funding for another entity, project, or activity.
-
C.
notFundedBy
Indicates that one entity does not receive financial support, backing, or funding from another entity.
-
D.
funderType
Indicates the category or kind of organization or individual that provides funding in the relationship.
-
E.
fundingContext
Indicates the circumstances, purpose, or conditions under which funding is provided or used in a given relationship or action.
- 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_69a88a1a4a6081908645b0f2914521ab |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc749f8e0819094144b9dd9db8790 |
completed | March 7, 2026, 6:35 a.m. |
| PD | Predicate disambiguation | batch_69abc59b88348190a2d6c08f69974117 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:55 p.m.