Triple
T136418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GM Defense |
E2756
|
entity |
| Predicate | products |
P3585
|
FINISHED |
| Object | military vehicles |
—
|
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: military vehicles | Statement: [GM Defense, products, military vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: products Context triple: [GM Defense, products, military vehicles]
-
A.
produces
Indicates that one entity creates, generates, or yields another entity as a result or output.
-
B.
hasProduct
chosen
Indicates that an entity possesses, offers, or is associated with a particular product.
-
C.
notableProduct
Indicates that a product is especially significant, prominent, or well-known in relation to the associated entity.
-
D.
commodity
Indicates that one entity is a tradable good or resource that is bought, sold, or exchanged in relation to another entity.
-
E.
platforms
Indicates that one entity provides or serves as a base, medium, or environment that supports the operation, distribution, or presentation of another 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a4edf081908c494c8370c76b9a |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a25652efdc8190b85b33735a9e6370 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.