Triple
T25388043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stryker brigade combat team |
E631577
|
entity |
| Predicate | usesVehicleVariant |
P158481
|
FINISHED |
| Object | Stryker Reconnaissance Vehicle |
—
|
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: Stryker Reconnaissance Vehicle | Statement: [Stryker brigade combat team, usesVehicleVariant, Stryker Reconnaissance Vehicle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesVehicleVariant Context triple: [Stryker brigade combat team, usesVehicleVariant, Stryker Reconnaissance Vehicle]
-
A.
resultedInVehicleVariant
Indicates that one event, process, or action led to the creation or emergence of a specific variant of a vehicle.
-
B.
carTypeVariant
Indicates that one car type is a specific variant or version of another car type.
-
C.
introducedOnVehicleVariant
Indicates that a feature, component, or change was first introduced or became available on a specific vehicle variant.
-
D.
basedOnVehicle
Indicates that one entity is derived from, modeled after, or otherwise conceptually or functionally based on a particular vehicle.
-
E.
hasVehicularUse
Indicates that something is used for, intended for, or associated with operation by vehicles or vehicular traffic.
- 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_69e75a8c50788190aabaa9f96710fc43 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f5656c16ac8190be99d40cb63f9541 |
completed | May 2, 2026, 2:46 a.m. |
| PD | Predicate disambiguation | batch_69f4683b34748190818428489a226124 |
completed | May 1, 2026, 8:45 a.m. |
| PDg | Predicate description generation | batch_69f46d361c348190b5fdfd805ecde01b |
completed | May 1, 2026, 9:07 a.m. |
Created at: April 21, 2026, 1:47 p.m.