Triple
T136010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holden |
E2747
|
entity |
| Predicate | brandType |
P1500
|
FINISHED |
| Object | mass-market brand |
—
|
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: mass-market brand | Statement: [Holden, brandType, mass-market brand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brandType Context triple: [Holden, brandType, mass-market brand]
-
A.
brand
chosen
Indicates that one entity is the commercial brand or label under which another entity (such as a product, service, or organization) is marketed or identified.
-
B.
formerBrand
Indicates that an entity was previously used or recognized as a brand for another entity but is no longer its current brand.
-
C.
sponsorType
Indicates the specific role or category of sponsorship that an entity provides in relation to another entity or event.
-
D.
manufacturedBy
Indicates that an item or product is produced or created by a specific manufacturer or maker.
-
E.
brakeType
Indicates the specific kind or system of brakes associated with an 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_69a25651b9048190a6277b7fec98c1ea |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.