Triple
T6942249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aquasource line |
E160705
|
entity |
| Predicate | associatedBrand |
P1500
|
FINISHED |
| Object | L’Oréal Group |
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: L’Oréal Group | Statement: [Aquasource line, associatedBrand, L’Oréal Group]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: L’Oréal Group Context triple: [Aquasource line, associatedBrand, L’Oréal Group]
-
A.
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.
-
B.
Estée Lauder Companies
Estée Lauder Companies is a leading global cosmetics and skincare conglomerate that owns numerous prestigious beauty brands across makeup, fragrance, haircare, and skincare.
-
C.
Coty Inc.
Coty Inc. is a global beauty company known for its extensive portfolio of cosmetics, skincare, and fragrance brands.
-
D.
Lancôme
Lancôme is a French luxury cosmetics and skincare brand renowned for its high-end perfumes, makeup, and beauty products.
-
E.
Unilever
Unilever is a multinational consumer goods company known for its wide range of food, personal care, and household products sold globally.
- 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_69c6884f3db4819080ad65da69386206 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da85f43881909549ac26b3db135a |
completed | March 27, 2026, 7:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7a30c94fc8190b5994a7dc2b709c0 |
completed | March 28, 2026, 9:44 a.m. |
Created at: March 27, 2026, 2:28 p.m.