Triple
T3428365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diesel (licensed watches) |
E72278
|
entity |
| Predicate | brandAesthetic |
P15065
|
FINISHED |
| Object | urban |
—
|
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: urban | Statement: [Diesel (licensed watches), brandAesthetic, urban]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brandAesthetic Context triple: [Diesel (licensed watches), brandAesthetic, urban]
-
A.
brandingFeature
Indicates that one entity serves as a branding-related characteristic, element, or attribute that helps define or distinguish another entity’s brand identity.
-
B.
brandAttribute
chosen
Indicates that a specific attribute or characteristic is associated with, or describes, a particular brand.
-
C.
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.
-
D.
brandPositioning
Indicates how a brand is strategically placed and perceived in the minds of its target audience relative to competitors.
-
E.
brandFocus
Indicates that a brand primarily concentrates its efforts, messaging, or resources on a particular target, theme, or market segment.
- 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_69ad85ae14308190bcbc25cfa0246c0b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb983f4608190abcc27aa7b926deb |
completed | March 8, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69adadfea024819094b41a13bc004bda |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:15 p.m.