Triple
T4856211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ares armoured personnel carrier |
E108541
|
entity |
| Predicate | hasSensorSuite |
P17204
|
FINISHED |
| Object | situational awareness cameras |
—
|
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: situational awareness cameras | Statement: [Ares armoured personnel carrier, hasSensorSuite, situational awareness cameras]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSensorSuite Context triple: [Ares armoured personnel carrier, hasSensorSuite, situational awareness cameras]
-
A.
hasSensor
chosen
Indicates that one entity is equipped with, contains, or uses a particular sensor.
-
B.
hasHardwareCompatibilityWith
Indicates that two hardware components or systems can operate together correctly and reliably without conflicts or incompatibilities.
-
C.
hasCalibration
Indicates that an entity is associated with or uses a specific calibration configuration, setting, or procedure.
-
D.
hasSimulator
Indicates that one entity provides or is associated with a simulator used to model, emulate, or test the behavior of another entity.
-
E.
hasFingerprintSensor
Indicates that an entity is equipped with or includes a fingerprint recognition sensor.
- 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_69bd440a89548190a5f14ba6da6b97dc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2557388190a2d15571bacd24f3 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:26 p.m.