Triple
T895375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Presidential Libraries |
E19331
|
entity |
| Predicate | operatingCostsFundedBy |
P67
|
FINISHED |
| Object | federal appropriations |
—
|
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: federal appropriations | Statement: [Presidential Libraries, operatingCostsFundedBy, federal appropriations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatingCostsFundedBy Context triple: [Presidential Libraries, operatingCostsFundedBy, federal appropriations]
-
A.
fundedBy
chosen
Indicates that an entity receives financial support or resources from another entity.
-
B.
operatesFund
Indicates that an entity manages and runs the activities or investments of a particular fund.
-
C.
recoversCostsVia
Indicates that one party regains or offsets its incurred costs through a specified mechanism, source, or intermediary.
-
D.
operatesBy
Indicates that an entity performs its function, action, or process through the use or application of another entity (e.g., a method, mechanism, or principle).
-
E.
fundingModel
Indicates how an entity is financially supported or sustained, such as through specific revenue sources, payment structures, or funding mechanisms.
- 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_69a4939d37188190848be3d426ebc9ae |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad23d6e88190a2fb5e1e168a7b44 |
completed | March 1, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69a4aa94f7c881908deeb62308942e19 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.