Triple
T15756323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VHF |
E381975
|
entity |
| Predicate | typicalServiceAllocation |
P77513
|
FINISHED |
| Object | 30–88 MHz military land mobile |
—
|
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: 30–88 MHz military land mobile | Statement: [VHF, typicalServiceAllocation, 30–88 MHz military land mobile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalServiceAllocation Context triple: [VHF, typicalServiceAllocation, 30–88 MHz military land mobile]
-
A.
allocationType
chosen
Indicates the specific manner or category by which resources, responsibilities, or items are assigned or distributed among entities.
-
B.
typicalServiceRequirement
Indicates that a certain condition, resource, or specification is normally needed or expected for a service to be properly provided or operated.
-
C.
typicalServiceStatus
Indicates the usual or standard operational state or condition that a service is expected to be in under normal circumstances.
-
D.
typicalDeployment
Indicates that one entity represents the standard or most commonly used deployment configuration or pattern for the other entity.
-
E.
servedByService
Indicates that something is provided, handled, or fulfilled by a particular service.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b1ff4881909d5240d1d30f5c8b |
completed | April 16, 2026, 3 a.m. |
| PD | Predicate disambiguation | batch_69e00531e7ac8190a4190cce4f7fab4c |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:47 a.m.