Triple
T8729808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pionierpanzer 2 |
E207222
|
entity |
| Predicate | hasAuxiliaryEquipment |
P84313
|
FINISHED |
| Object | various engineering tools |
—
|
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: various engineering tools | Statement: [Pionierpanzer 2, hasAuxiliaryEquipment, various engineering tools]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAuxiliaryEquipment Context triple: [Pionierpanzer 2, hasAuxiliaryEquipment, various engineering tools]
-
A.
hasBaggageSystem
Indicates that an entity is equipped with or utilizes a baggage handling system.
-
B.
hasAirComponent
Indicates that something includes, contains, or is associated with an air-related component or element.
-
C.
notableGroundEquipment
Indicates that there is ground-based equipment at or associated with an entity that is considered significant or noteworthy in some context.
-
D.
fleetIncludes
Indicates that a particular fleet contains or is composed of the specified entity or entities as its members.
-
E.
hasVehicleDeck
Indicates that something (typically a vessel or structure) includes a dedicated deck or level designed for carrying or transporting vehicles.
- 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_69ca8358e4008190898471a59b96c301 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d19fdc88190860e0c9c93ab79ce |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457093188190959287a6458651c6 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc489dd528819084ed5d88bd8bb3d6 |
completed | March 31, 2026, 10:20 p.m. |
Created at: March 30, 2026, 6:37 p.m.