Triple
T2403679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenvue |
E50225
|
entity |
| Predicate | ownsBrand |
P1500
|
FINISHED |
| Object | Neutrogena |
E49849
|
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: Neutrogena | Statement: [Kenvue, ownsBrand, Neutrogena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neutrogena Context triple: [Kenvue, ownsBrand, Neutrogena]
-
A.
Neutrogena
chosen
Neutrogena is a widely recognized skincare and cosmetics brand known for its dermatologist-recommended products, including facial cleansers, moisturizers, sunscreens, and acne treatments.
-
B.
Clinique
Clinique is an American skincare and cosmetics brand known for its dermatologist-developed, fragrance-free products and clinical approach to beauty.
-
C.
La Roche-Posay
La Roche-Posay is a French dermatological skincare brand known for its sensitive-skin-friendly formulas developed with thermal spring water and widely recommended by dermatologists.
-
D.
Kiehl's
Kiehl's is an American skincare and cosmetics brand known for its apothecary-style stores and science-driven formulations.
-
E.
Biotherm
Biotherm is a French skincare brand known for its use of aquatic ingredients and scientifically driven formulas for face and body care.
- 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc8f8aa2881909192920ee394f0b3 |
completed | March 7, 2026, 6:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aeb3e740c88190872aa1a7834d73b0 |
completed | March 9, 2026, 11:49 a.m. |
Created at: March 4, 2026, 7:58 p.m.