Triple
T2320493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sd.Kfz. 251 |
E51167
|
entity |
| Predicate | armorThicknessRange |
P9690
|
FINISHED |
| Object | 6–14.5 mm |
—
|
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: 6–14.5 mm | Statement: [Sd.Kfz. 251, armorThicknessRange, 6–14.5 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armorThicknessRange Context triple: [Sd.Kfz. 251, armorThicknessRange, 6–14.5 mm]
-
A.
deckArmorThickness
Indicates the thickness of the armor plating on the horizontal deck surface of a vehicle, vessel, or structure.
-
B.
armorTurretFaceThickness
Indicates the thickness of the armor on the front-facing surface of a turret.
-
C.
armorType
Indicates the specific category or classification of protective armor associated with an entity.
-
D.
thickness
chosen
Indicates the measure of how deep or wide an object or layer is from one surface or side to its opposite.
-
E.
frontArmorRange
Indicates the range or extent of protective armor coverage on the front-facing side of an entity.
- 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_69a88b074b908190ae983dbca7757d88 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc5909cc48190aab257313542dc49 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.