Triple
T25369353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Armani Beauty |
E632888
|
entity |
| Predicate | usesLogoStyle |
P140819
|
FINISHED |
| Object | Giorgio Armani wordmark |
—
|
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: Giorgio Armani wordmark | Statement: [Armani Beauty, usesLogoStyle, Giorgio Armani wordmark]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLogoStyle Context triple: [Armani Beauty, usesLogoStyle, Giorgio Armani wordmark]
-
A.
hasLogoStyle
chosen
Indicates that an entity’s logo possesses or is characterized by a particular visual style or design approach.
-
B.
logoUsedIn
Indicates that a particular logo is employed or displayed within a specified context, medium, or artifact.
-
C.
logoUsedBy
Indicates that a particular logo is employed or displayed by a specific entity as part of its identity, branding, or representation.
-
D.
hasLogoText
Indicates that an entity’s logo includes specific textual content or wording.
-
E.
usedStyle
Indicates that one entity employed or applied a particular style, method, or manner associated with another 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_69e75a90c0dc819092f928b6ea0ecc72 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f5f6baf2d48190a6a4cd6501be87d2 |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 21, 2026, 1:38 p.m.