Triple
T36835727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VK 45.01 (H) |
E910265
|
entity |
| Predicate | turretSupplier |
P165517
|
FINISHED |
| Object | Krupp (planned) |
—
|
NE NERFINISHED |
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: Krupp (planned) | Statement: [VK 45.01 (H), turretSupplier, Krupp (planned)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turretSupplier Context triple: [VK 45.01 (H), turretSupplier, Krupp (planned)]
-
A.
turretManufacturer
chosen
Indicates that one entity is the manufacturer or producer of a turret associated with another entity.
-
B.
turretBasedOn
Indicates that one turret is derived from, modeled after, or constructed using the design or components of another turret.
-
C.
turret
Indicates that an entity is equipped with or associated with a turret, typically a rotating weapon or defense mechanism.
-
D.
turretDesign
Indicates a relationship where one entity specifies or defines the design or configuration of a turret associated with another entity.
-
E.
turretCount
Indicates the number of turrets associated with or mounted on a given 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_69f76e7e9d60819092442fba73290a46 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:13 p.m.