Triple
T33666327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jagdpanzer IV early variants |
E862502
|
entity |
| Predicate | superstructureFrontArmorThickness |
P191114
|
FINISHED |
| Object | 60 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: 60 mm | Statement: [Jagdpanzer IV early variants, superstructureFrontArmorThickness, 60 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: superstructureFrontArmorThickness Context triple: [Jagdpanzer IV early variants, superstructureFrontArmorThickness, 60 mm]
-
A.
frontHullArmorThickness
Indicates the thickness of the armor located on the front section of a vehicle’s hull.
-
B.
sideArmorThickness
Indicates the thickness of an object's armor specifically along its sides.
-
C.
armourThickness
Indicates the measured thickness of an entity’s protective armor in the context of defense or shielding.
-
D.
deckArmorThickness
Indicates the thickness of the armor plating on the horizontal deck surface of a vehicle, vessel, or structure.
-
E.
armourThicknessMin
Indicates the minimum measured or specified thickness of an object's armor in the described context.
- 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_69f34984c4008190bb82f33a7819da64 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fcda3699948190adb57625bae08091 |
completed | May 7, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fd16d08190b0aca6e19a632e99 |
completed | May 7, 2026, 6:25 p.m. |
| PDg | Predicate description generation | batch_69fcda35dc048190a3c90e15230900e0 |
completed | May 7, 2026, 6:30 p.m. |
Created at: May 1, 2026, 1:42 a.m.