Triple
T11969939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Armand Petitjean |
E284890
|
entity |
| Predicate | brandCreated |
P5261
|
FINISHED |
| Object | Lancôme |
E27682
|
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: Lancôme | Statement: [Armand Petitjean, brandCreated, Lancôme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lancôme Context triple: [Armand Petitjean, brandCreated, Lancôme]
-
A.
Lancôme
chosen
Lancôme is a French luxury cosmetics and skincare brand renowned for its high-end perfumes, makeup, and beauty products.
-
B.
Yves Saint Laurent Beauté
Yves Saint Laurent Beauté is a luxury cosmetics and fragrance brand known for its high-end makeup, skincare, and iconic perfumes.
-
C.
Dior Beauty
Dior Beauty is the cosmetics and fragrance division of the French luxury fashion house Dior, known for its high-end makeup, skincare, and perfumes.
-
D.
Estée Lauder
Estée Lauder was an American businesswoman and co-founder of the Estée Lauder cosmetics company, renowned for building one of the world’s leading beauty empires.
-
E.
Armani Beauty
Armani Beauty is the cosmetics and fragrance line of the Giorgio Armani fashion house, known for its luxurious makeup, skincare, and signature perfumes.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9037bee54819085242a3ef3e286f9 |
completed | April 10, 2026, 2:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f48a9628cc819095d15fd90023e57d |
completed | May 1, 2026, 11:12 a.m. |
Created at: April 8, 2026, 9:46 p.m.