Triple
T3128141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kardashian–Jenner brand |
E65345
|
entity |
| Predicate | hasBusinessSegment |
P1670
|
FINISHED |
| Object | KKW Beauty |
E83326
|
NE 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: KKW Beauty | Statement: [Kardashian–Jenner brand, hasBusinessSegment, KKW Beauty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KKW Beauty Context triple: [Kardashian–Jenner brand, hasBusinessSegment, KKW Beauty]
-
A.
KKW Beauty
chosen
KKW Beauty is a cosmetics brand founded by media personality Kim Kardashian, known for its contouring products, neutral-toned palettes, and social media–driven marketing.
-
B.
Kiehl's
Kiehl's is an American skincare and cosmetics brand known for its apothecary-style stores and science-driven formulations.
-
C.
Maybelline New York
Maybelline New York is a major American cosmetics and beauty brand known worldwide for its mass-market makeup products.
-
D.
NYX Professional Makeup
NYX Professional Makeup is a popular, affordable cosmetics brand known for its wide range of highly pigmented, trend-driven makeup products favored by both professionals and everyday consumers.
-
E.
CoverGirl
CoverGirl is a major American cosmetics brand known for its mass-market makeup products and high-profile celebrity spokesmodels.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ad8580c72481909672d37acf647893 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada546a6648190bc4bc3e599e6aa95 |
completed | March 8, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f7926248190b8f08e3a626e8eab |
completed | March 12, 2026, 12:57 a.m. |
Created at: March 8, 2026, 3:04 p.m.