Triple
T2974573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panzer III |
E80361
|
entity |
| Predicate | armourThickness |
P44334
|
FINISHED |
| Object | up to 70 mm on later variants |
—
|
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: up to 70 mm on later variants | Statement: [Panzer III, armourThickness, up to 70 mm on later variants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armourThickness Context triple: [Panzer III, armourThickness, up to 70 mm on later variants]
-
A.
deckArmorThickness
Indicates the thickness of the armor plating on the horizontal deck surface of a vehicle, vessel, or structure.
-
B.
sideArmorThickness
Indicates the thickness of an object's armor specifically along its sides.
-
C.
armoredBeltThickness
Indicates the thickness of an entity’s protective armored belt in the context of its defensive structure or design.
-
D.
armour
Indicates that an entity provides protective covering or defense for another entity.
-
E.
armourBelt
Indicates a relationship where an armour belt is equipped on, attached to, or associated with an entity (such as a character, vehicle, or structure) as protective gear.
- F. None of above. chosen
Provenance (4 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_69ad8b14ffe881908ffed62f9595c867 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99894bb0819099fa5cc5166c0eeb |
completed | March 8, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69ad96105a708190a9ec4838cbcb1207 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f5d28c8190899d90204dc43428 |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:58 p.m.