Triple
T14074897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beast Mode apparel brand |
E338705
|
entity |
| Predicate | hasBrandAesthetic |
P102534
|
FINISHED |
| Object | bold |
—
|
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: bold | Statement: [Beast Mode apparel brand, hasBrandAesthetic, bold]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBrandAesthetic Context triple: [Beast Mode apparel brand, hasBrandAesthetic, bold]
-
A.
hasBrandConcept
Indicates that an entity is associated with or embodies a particular brand concept or branding idea.
-
B.
hasBrandType
Indicates that an entity is associated with or categorized under a particular brand type or classification.
-
C.
associatedAesthetic
chosen
Indicates a relationship where one entity is linked to or characterized by a particular aesthetic style, quality, or visual/theme-based sensibility.
-
D.
hasBrandName
Indicates that an entity is associated with or identified by a specific brand name.
-
E.
hasBrandIdentityElement
Indicates that an entity includes or is associated with a specific component of its overall brand identity (such as a logo, color scheme, or tagline).
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5c5bc49881909012b66fa451f495 |
completed | April 14, 2026, 3:25 p.m. |
| PD | Predicate disambiguation | batch_69de05b0e6c88190a819eeba0028981f |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:21 p.m.