Triple
T35683216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bruneau, Idaho |
E1031067
|
entity |
| Predicate | nearestAirForceBase |
P184071
|
FINISHED |
| Object | Mountain Home Air Force Base |
—
|
NE NERFINISHED |
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: Mountain Home Air Force Base | Statement: [Bruneau, Idaho, nearestAirForceBase, Mountain Home Air Force Base]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearestAirForceBase Context triple: [Bruneau, Idaho, nearestAirForceBase, Mountain Home Air Force Base]
-
A.
nearestAirport
Indicates that one airport is the closest in distance to a given location or entity compared to all other airports.
-
B.
nearestNavalInstallation
Indicates that one entity is the closest naval installation in distance or proximity to another specified location or entity.
-
C.
nearestLargerAirport
Indicates that one airport is the closest geographically among all airports that are larger (e.g., by traffic or capacity) than a given reference airport.
-
D.
nearMilitaryInstallation
Indicates that one entity is located in close physical proximity to a military installation or facility.
-
E.
nearbyAirportRelationship
Indicates that one location has an airport situated close enough to serve it conveniently, establishing a nearby-airport relationship between the two.
- 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_69f76e0bb6608190ad3a1880be54a17d |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aaabb58c8190bf81673608ecfb6e |
completed | May 3, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d219f8819081dc4ce3c83ca0cb |
completed | May 3, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f7aa6795f481908940838ee7041ff5 |
completed | May 3, 2026, 8:04 p.m. |
Created at: May 3, 2026, 4:05 p.m.