Triple
T2579437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oahu |
E57052
|
entity |
| Predicate | hasLargestMilitaryPresenceInHawaii |
P40388
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Oahu, hasLargestMilitaryPresenceInHawaii, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLargestMilitaryPresenceInHawaii Context triple: [Oahu, hasLargestMilitaryPresenceInHawaii, true]
-
A.
hasMilitaryPresence
Indicates that a military force is present in, stationed at, or operating within a particular location or entity.
-
B.
hasMilitaryBase
Indicates that one entity possesses, hosts, or contains a military base associated with or located on another entity.
-
C.
populationRankInHawaii
Indicates the relative position of an entity in terms of population size compared to other entities within Hawaii.
-
D.
servesAsNavalAirStationFor
Indicates that one entity functions as a naval air station providing aviation facilities and support for another entity (such as a navy, fleet, or military force).
-
E.
largestNavalBaseIn
Indicates that one entity is the largest naval base located within the specified geographic or political region.
- 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3a9fd3c8190a521931e40cd801c |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0cfeae08190aed03866ba071c5c |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd209d934819093600889af9104c3 |
completed | March 7, 2026, 7:21 a.m. |
Created at: March 6, 2026, 9:49 p.m.