Triple
T1292517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Professional Products Division |
E27577
|
entity |
| Predicate | brandPortfolio |
P12124
|
FINISHED |
| Object | Kérastase |
E4816
|
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: Kérastase | Statement: [Professional Products Division, brandPortfolio, Kérastase]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kérastase Context triple: [Professional Products Division, brandPortfolio, Kérastase]
-
A.
Redken
Redken is a professional haircare and hair color brand known for its salon-quality products and innovative, science-driven formulas.
-
B.
Schwarzkopf
Schwarzkopf is a German surname most prominently associated with U.S. Army General Norman Schwarzkopf Jr., who led coalition forces in the Gulf War.
-
C.
Biotherm
Biotherm is a French skincare brand known for its use of aquatic ingredients and scientifically driven formulas for face and body care.
-
D.
L'Oréal
chosen
L'Oréal is a French multinational cosmetics and beauty company recognized as one of the world’s largest and most influential personal care brands.
-
E.
Kiehl's
Kiehl's is an American skincare and cosmetics brand known for its apothecary-style stores and science-driven formulations.
- 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0f09d5c81909e6dc036fe9c5b4a |
completed | March 1, 2026, 10:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acb300d3a0819081a9d19ea1fbdfe2 |
completed | March 7, 2026, 11:21 p.m. |
Created at: March 1, 2026, 7:51 p.m.