Triple
T16824855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baxley, Georgia |
E408991
|
entity |
| Predicate | hasNearbyInfrastructureType |
P124983
|
FINISHED |
| Object | energy 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: energy infrastructure | Statement: [Baxley, Georgia, hasNearbyInfrastructureType, energy infrastructure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyInfrastructureType Context triple: [Baxley, Georgia, hasNearbyInfrastructureType, energy infrastructure]
-
A.
hasNearbySiteType
Indicates that one entity has another entity of a specified site type located in its close physical vicinity.
-
B.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
C.
hasNearbyLandUse
Indicates that one land area is located close to another area characterized by a specific type of land use.
-
D.
adjacentToInfrastructure
Indicates that one entity is located directly next to or in immediate proximity to a piece of infrastructure.
-
E.
hasNearbyCivicBuilding
Indicates that one entity is located close to, or in the immediate vicinity of, a civic building such as a government, public service, or community facility.
- F. None of above. chosen
Provenance (4 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b310ffec81908087e5aaacc4a7c2 |
completed | April 18, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_69e32b814b188190aee525f8779203cd |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e34fb7c8c8819086975b7955b7d8ef |
completed | April 18, 2026, 9:32 a.m. |
Created at: April 10, 2026, 5:23 a.m.