Triple
T13590764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sephora |
E324685
|
entity |
| Predicate | hasPrivateLabelBrand |
P11989
|
FINISHED |
| Object | Sephora Collection |
E324685
|
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: Sephora Collection | Statement: [Sephora, hasPrivateLabelBrand, Sephora Collection]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sephora Collection Context triple: [Sephora, hasPrivateLabelBrand, Sephora Collection]
-
A.
Sephora
Sephora is a character in the 1956 biblical epic film "The Ten Commandments," depicted as Moses' Midianite wife Zipporah.
-
B.
Sephora
chosen
Sephora is a global beauty retail chain known for its wide selection of cosmetics, skincare, and fragrance brands and its experiential, try-before-you-buy store concept.
-
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.
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.
-
E.
Harrods Beauty
Harrods Beauty is the luxury beauty and cosmetics department of the Harrods department store, offering high-end skincare, makeup, fragrance, and related services.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb055cc98819091fab597b69e5e3e |
completed | April 12, 2026, 2:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76bc578908190abd5cca94b1c3a5c |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.