Triple
T2439424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | StuG III |
E53237
|
entity |
| Predicate | isMostProducedGermanAFV |
P39338
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [StuG III, isMostProducedGermanAFV, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMostProducedGermanAFV Context triple: [StuG III, isMostProducedGermanAFV, true]
-
A.
germanUnit
Indicates that an entity is a military or organizational unit that belongs to, originates from, or is associated with Germany.
-
B.
isMilitaryVariantOf
Indicates that one entity is a military-specific version or adaptation of another, typically civilian or general-purpose, entity.
-
C.
primaryGermanFighterAircraft
Indicates that the subject is the main or principal fighter aircraft used by Germany in a given context or time period.
-
D.
primaryGermanBomberAircraft
Indicates that the subject is the main type of bomber aircraft used by Germany in a given context or period.
-
E.
typeOfWeaponsProduced
Indicates the specific categories or kinds of weapons that are manufactured or produced by an entity.
- 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_69ab495b6dac8190ac82661aa1452222 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcebf7cac8190889e6890d72c256c |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5ac11b081908ce6a506e81a742a |
completed | March 7, 2026, 6:29 a.m. |
| PDg | Predicate description generation | batch_69abcebe7dd08190b197a2a0e78787e3 |
completed | March 7, 2026, 7:07 a.m. |
Created at: March 6, 2026, 9:43 p.m.