Triple
T31792591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Navy anti-submarine squadrons |
E811509
|
entity |
| Predicate | typicalSensor |
—
|
GENERATED |
| Object | airborne radar |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSensor Context triple: [U.S. Navy anti-submarine squadrons, typicalSensor, airborne radar]
-
A.
hasSensor
chosen
Indicates that one entity is equipped with, contains, or uses a particular sensor.
-
B.
sensorClass
Indicates that one entity is classified as a type or category of sensor relative to another entity.
-
C.
trackingSensor
Indicates that a sensor is monitoring, recording, or following the state, position, or behavior of a target entity over time.
-
D.
basicSense
Indicates that one entity represents the most fundamental or primary meaning or interpretation of another entity.
-
E.
sensorTypesInvolved
Indicates the types of sensors that participate in or are utilized within a given event, process, or system.
- F. None of above.
Provenance (1 batch)
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_69f348e60748819082dcaa7792659803 |
completed | April 30, 2026, 12:19 p.m. |
Created at: April 30, 2026, 11:39 p.m.