Triple
T215739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L'Oréal |
E4816
|
entity |
| Predicate | ownsBrand |
P1500
|
FINISHED |
| Object |
Garnier
Garnier is a global mass-market cosmetics and personal care brand known for its haircare, skincare, and color products.
|
E4816
|
NE FINISHED |
How this triple was built (4 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: Garnier | Statement: [L'Oréal, ownsBrand, Garnier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garnier Context triple: [L'Oréal, ownsBrand, Garnier]
-
A.
Lancôme
Lancôme is a French luxury cosmetics and skincare brand renowned for its high-end perfumes, makeup, and beauty products.
-
B.
L'Oréal
L'Oréal is a French multinational cosmetics and beauty company recognized as one of the world’s largest and most influential personal care brands.
-
C.
Elizabeth Arden
Elizabeth Arden was a pioneering Canadian-American businesswoman who founded the Elizabeth Arden cosmetics empire and helped shape the modern beauty industry.
-
D.
Redken
Redken is a professional haircare and hair color brand known for its salon-quality products and innovative, science-driven formulas.
-
E.
Gillette
Gillette is a globally recognized American brand best known for its razors and shaving products.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Garnier Triple: [L'Oréal, ownsBrand, Garnier]
Generated description
Garnier is a global mass-market cosmetics and personal care brand known for its haircare, skincare, and color products.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Garnier Target entity description: Garnier is a global mass-market cosmetics and personal care brand known for its haircare, skincare, and color products.
-
A.
Lancôme
Lancôme is a French luxury cosmetics and skincare brand renowned for its high-end perfumes, makeup, and beauty products.
-
B.
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.
-
C.
Elizabeth Arden
Elizabeth Arden was a pioneering Canadian-American businesswoman who founded the Elizabeth Arden cosmetics empire and helped shape the modern beauty industry.
-
D.
Redken
Redken is a professional haircare and hair color brand known for its salon-quality products and innovative, science-driven formulas.
-
E.
Gillette
Gillette is a globally recognized American brand best known for its razors and shaving products.
- F. None of above.
Provenance (5 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c4ca0c8819093f63c6371e2d140 |
completed | Feb. 28, 2026, 3:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a34766506c8190a4c661410e0d8b33 |
completed | Feb. 28, 2026, 7:52 p.m. |
| NEDg | Description generation | batch_69a34c38fc2881908afe5d3ef34db98e |
completed | Feb. 28, 2026, 8:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a34ca4faec8190bd09fa0e87fe0bd5 |
completed | Feb. 28, 2026, 8:14 p.m. |
Created at: Feb. 28, 2026, 2:52 a.m.