Triple
T4663133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lily-Rose Depp |
E102780
|
entity |
| Predicate | hasModeledFor |
P17880
|
FINISHED |
| Object | Chanel |
E55550
|
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: Chanel | Statement: [Lily-Rose Depp, hasModeledFor, Chanel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chanel Context triple: [Lily-Rose Depp, hasModeledFor, Chanel]
-
A.
Chanel
chosen
Chanel is a legendary French luxury fashion house renowned for its haute couture, ready-to-wear, handbags, fragrances, and timeless designs such as the Chanel No. 5 perfume and the classic tweed suit.
-
B.
Givenchy
Givenchy is a renowned French luxury fashion and perfume house known for its haute couture, ready-to-wear collections, and iconic collaborations with celebrities and models.
-
C.
Nina Ricci
Nina Ricci is a French luxury fashion house renowned for its elegant haute couture, ready-to-wear collections, and iconic fragrances.
-
D.
Louis Vuitton
Louis Vuitton is a French luxury fashion house and brand renowned worldwide for its high-end leather goods, ready-to-wear, accessories, and iconic monogram designs.
-
E.
Chloé
Chloé is a French luxury fashion house renowned for its feminine ready-to-wear, leather goods, and accessories.
- 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_69bd43d9cba4819086c1ab1c2d9d2133 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd632d6150819085bab97021c0235a |
completed | March 20, 2026, 3:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfafe60548190ae00b13dcdacebcd |
completed | March 21, 2026, 1:57 a.m. |
Created at: March 20, 2026, 1:15 p.m.