Triple
T26180080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niihau |
E654649
|
entity |
| Predicate | militaryUseNearby |
P146261
|
FINISHED |
| Object | Pacific Missile Range Facility (offshore) |
—
|
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: Pacific Missile Range Facility (offshore) | Statement: [Niihau, militaryUseNearby, Pacific Missile Range Facility (offshore)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militaryUseNearby Context triple: [Niihau, militaryUseNearby, Pacific Missile Range Facility (offshore)]
-
A.
nearMilitaryInstallation
Indicates that one entity is located in close physical proximity to a military installation or facility.
-
B.
hasFormerMilitaryInstallationNearby
Indicates that an entity is located close to a site where a military installation previously existed but is no longer active.
-
C.
hasNearbyMilitaryTrainingArea
Indicates that an entity is located close to a designated area used for military training activities.
-
D.
usedByMilitaryInstallations
chosen
Indicates that something is utilized or operated by military installations for their functions or activities.
-
E.
nearbyBattlefield
Indicates that one entity is located close to or in the immediate vicinity of a battlefield.
- 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_69ee5b45873c81909499203612d05d07 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a731508190bb0c8c2462eba224 |
completed | May 2, 2026, 7:33 p.m. |
Created at: April 26, 2026, 8:39 p.m.