Triple
T314056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leopard 2 |
E7668
|
entity |
| Predicate | crewPositions |
P2094
|
FINISHED |
| Object | commander |
—
|
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: commander | Statement: [Leopard 2, crewPositions, commander]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crewPositions Context triple: [Leopard 2, crewPositions, commander]
-
A.
crew
chosen
Indicates that one entity serves as the group of people who operate, staff, or work on another entity (such as a vehicle, vessel, or production).
-
B.
crewCountApproximate
Indicates that the relationship specifies an estimated or approximate number of crew members associated with an entity.
-
C.
turretCrew
Indicates that an entity serves as a crew member operating or manning a turret associated with another entity.
-
D.
umpireCrewChief
Indicates that one entity serves as the crew chief (lead umpire) for a particular umpire crew.
-
E.
peakPersonnel
Indicates the maximum number of personnel involved or present at any point during a specified period or activity.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea4bd6a081909bdb57602c7093b4 |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e9428098819089d5950cd2c96dc4 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:07 p.m.