Triple
T215747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L'Oréal |
E4816
|
entity |
| Predicate | ownsBrand |
P1500
|
FINISHED |
| Object |
Redken
Redken is a professional haircare and hair color brand known for its salon-quality products and innovative, science-driven formulas.
|
E27579
|
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: Redken | Statement: [L'Oréal, ownsBrand, Redken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Redken Context triple: [L'Oréal, ownsBrand, Redken]
-
A.
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.
-
B.
Gillette
Gillette is a globally recognized American brand best known for its razors and shaving products.
-
C.
CND
CND is a British peace organization best known for campaigning against nuclear weapons and promoting global disarmament.
-
D.
Elizabeth Arden
Elizabeth Arden was a pioneering Canadian-American businesswoman who founded the Elizabeth Arden cosmetics empire and helped shape the modern beauty industry.
-
E.
Eastman
Eastman is a given name most notably associated with the 19th-century American painter Eastman Johnson, a co-founder of the Metropolitan Museum of Art.
- 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: Redken Triple: [L'Oréal, ownsBrand, Redken]
Generated description
Redken is a professional haircare and hair color brand known for its salon-quality products and innovative, science-driven formulas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Redken Target entity description: Redken is a professional haircare and hair color brand known for its salon-quality products and innovative, science-driven formulas.
-
A.
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.
-
B.
Gillette
Gillette is a globally recognized American brand best known for its razors and shaving products.
-
C.
CND
CND is a British peace organization best known for campaigning against nuclear weapons and promoting global disarmament.
-
D.
Elizabeth Arden
Elizabeth Arden was a pioneering Canadian-American businesswoman who founded the Elizabeth Arden cosmetics empire and helped shape the modern beauty industry.
-
E.
Eastman
Eastman is a given name most notably associated with the 19th-century American painter Eastman Johnson, a co-founder of the Metropolitan Museum of Art.
- F. None of above. chosen
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_69a33e3f66888190a05ddcb0af4d3c5f |
completed | Feb. 28, 2026, 7:13 p.m. |
| NEDg | Description generation | batch_69a33ee88af08190bfe81fba01856829 |
completed | Feb. 28, 2026, 7:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a34295afa88190aae0d75a337967e3 |
completed | Feb. 28, 2026, 7:31 p.m. |
Created at: Feb. 28, 2026, 2:52 a.m.