Triple
T9349971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ole Henriksen |
E224990
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Sephora |
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 | Statement: [Ole Henriksen, associatedWith, Sephora]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sephora Context triple: [Ole Henriksen, associatedWith, Sephora]
-
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.
Bath & Body Works
Bath & Body Works is a major American retail chain specializing in scented personal care products, candles, and home fragrances, known for its mall-based stores and seasonal collections.
-
D.
Bluemercury
Bluemercury is a luxury beauty and spa retail chain in the United States known for offering high-end skincare, makeup, and spa services.
-
E.
L’Occitane
L’Occitane is the nickname of the French A20 motorway, a major north–south route linking central France to the southwest.
- 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_69ca842abfd48190949d71c3b86eeba8 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f1198b88190adc0b01f7c1be36e |
completed | April 1, 2026, 5 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0e43c31008190b542a9c5aa33f30e |
completed | April 4, 2026, 10:13 a.m. |
Created at: March 30, 2026, 7:41 p.m.