Triple
T19063601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CABEI |
E466597
|
entity |
| Predicate | sectorFinanced |
P32550
|
FINISHED |
| Object | infrastructure |
—
|
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: infrastructure | Statement: [CABEI, sectorFinanced, infrastructure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectorFinanced Context triple: [CABEI, sectorFinanced, infrastructure]
-
A.
fundedBy
Indicates that an entity receives financial support or resources from another entity.
-
B.
sectorBenefited
chosen
Indicates that a particular sector gains advantage, support, or positive impact from a given action, policy, resource, or entity.
-
C.
fundingContext
Indicates the circumstances, purpose, or conditions under which funding is provided or used in a given relationship or action.
-
D.
financedMission
Indicates that one entity provided financial resources to support or fund a particular mission undertaken by another entity.
-
E.
publiclyFunded
Indicates that the entity receives financial support from public sources such as government budgets or taxpayer funds.
- 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_69d8dd040fb881909af2a964f65ad208 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e196deac8190ad0406c616197e0b |
completed | April 20, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69e4b99f602881909eeb9c780597e0e6 |
completed | April 19, 2026, 11:16 a.m. |
Created at: April 10, 2026, 12:03 p.m.