Triple
T26623573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serious Skincare |
E668272
|
entity |
| Predicate | hasBrandSpokesperson |
P8470
|
FINISHED |
| Object | Jennifer Flavin |
—
|
NE NERFINISHED |
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: Jennifer Flavin | Statement: [Serious Skincare, hasBrandSpokesperson, Jennifer Flavin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBrandSpokesperson Context triple: [Serious Skincare, hasBrandSpokesperson, Jennifer Flavin]
-
A.
hasFictionalSpokesperson
Indicates that an entity is represented or promoted by a spokesperson who is a fictional or imaginary character.
-
B.
fashionBrandEndorsement
Indicates a relationship where a fashion brand formally supports, promotes, or is publicly associated with an entity (such as a person, product, or event) as an endorser.
-
C.
brandKnownFor
Indicates that a brand is widely recognized or associated with a particular product, service, quality, or characteristic.
-
D.
hasOfficialSpokespersons
chosen
Indicates that an entity is formally represented or spoken for by one or more designated spokespersons in an official capacity.
-
E.
hasBrandRole
Indicates that an entity holds a specific functional or organizational role in relation to a particular brand.
- 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_69ee9cff507c819092b95bf7219a702e |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f657f653448190a945b4751af8507d |
completed | May 2, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 27, 2026, 2:22 a.m.