Triple
T5861301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | (RED) |
E130279
|
entity |
| Predicate | hasBrandStyle |
P48662
|
FINISHED |
| Object | parentheses around the word RED |
—
|
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: parentheses around the word RED | Statement: [(RED), hasBrandStyle, parentheses around the word RED]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBrandStyle Context triple: [(RED), hasBrandStyle, parentheses around the word RED]
-
A.
hasBrandName
Indicates that an entity is associated with or identified by a specific brand name.
-
B.
hasBrandIdentityElement
chosen
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).
-
C.
hasBranding
Indicates that one entity carries, displays, or is associated with the brand identity of another entity.
-
D.
hasContractStyle
Indicates that one entity is associated with or characterized by a particular contract style or contractual format.
-
E.
usesBrandCharacter
Indicates that one entity employs or features another entity’s brand character (such as a mascot or branded persona) in its materials, products, or communications.
- 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_69c0084f3bb08190a7720f55f7aa4252 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03345ca0c819081c81148d054fed2 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:56 p.m.