Triple
T136071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wuling |
E2748
|
entity |
| Predicate | brandPositioning |
P5254
|
FINISHED |
| Object | value-oriented |
—
|
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: value-oriented | Statement: [Wuling, brandPositioning, value-oriented]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brandPositioning Context triple: [Wuling, brandPositioning, value-oriented]
-
A.
brand
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.
marketPosition
Indicates the relative standing or rank an entity holds within a specific market compared to its competitors.
-
D.
mediaMarket
Indicates a relationship where a media outlet or content provider serves, targets, or operates within a particular geographic or demographic market.
-
E.
sponsorType
Indicates the specific role or category of sponsorship that an entity provides in relation to another entity or event.
- 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_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. |
| PDg | Predicate description generation | batch_69a256c72f6c81909b619b90d829d86e |
completed | Feb. 28, 2026, 2:45 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.