Triple
T38152499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BAE Systems Hawk T2 |
E952791
|
entity |
| Predicate | hasSimulation |
P31906
|
FINISHED |
| Object | embedded training systems |
—
|
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: embedded training systems | Statement: [BAE Systems Hawk T2, hasSimulation, embedded training systems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSimulation Context triple: [BAE Systems Hawk T2, hasSimulation, embedded training systems]
-
A.
hasSimulator
chosen
Indicates that one entity provides or is associated with a simulator used to model, emulate, or test the behavior of another entity.
-
B.
hasEmotionSimulation
Indicates that an entity is capable of generating or exhibiting a simulated emotional state rather than a genuine one.
-
C.
supportsSIMInstruction
Indicates that one entity is capable of handling or executing a specified SIM (Subscriber Identity Module) instruction for another entity.
-
D.
hasSIMConfiguration
Indicates that an entity is associated with or assigned a specific SIM card configuration or setup.
-
E.
simulationMethod
Indicates the technique or approach used to perform or implement a simulation.
- 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_69f76f0a67f4819080c492f61d688fcc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fe96c2647c819082989f11e1ae3d35 |
completed | May 9, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69fe928615448190af939e5a94be55bb |
completed | May 9, 2026, 1:48 a.m. |
Created at: May 3, 2026, 4:21 p.m.