Triple
T12451853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lux |
E297550
|
entity |
| Predicate | hasBrandSloganTheme |
P87955
|
FINISHED |
| Object | beauty and glamour |
—
|
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: beauty and glamour | Statement: [Lux, hasBrandSloganTheme, beauty and glamour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBrandSloganTheme Context triple: [Lux, hasBrandSloganTheme, beauty and glamour]
-
A.
hasAdvertisingSlogan
Indicates that an entity uses or is associated with a particular advertising slogan as part of its promotional or branding activities.
-
B.
sloganUsedBy
Indicates that a particular slogan is employed or adopted by a specific entity (such as a person, organization, or brand) in its communication or branding.
-
C.
hasSloganType
Indicates the specific category or type of slogan associated with an entity.
-
D.
hasBrandConcept
chosen
Indicates that an entity is associated with or embodies a particular brand concept or branding idea.
-
E.
sloganUsedIn
Indicates that a particular slogan is employed or featured within a specific context, such as a campaign, advertisement, or organization.
- 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95151e7348190a1d4953a8b416a13 |
completed | April 10, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69d94d3c27a08190a0237200203e476d |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.