Triple
T20071665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gigi Hadid |
E499752
|
entity |
| Predicate | hasModeledFor |
P17880
|
FINISHED |
| Object | Givenchy |
—
|
NE NERFINISHED |
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: Givenchy | Statement: [Gigi Hadid, hasModeledFor, Givenchy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Givenchy Context triple: [Gigi Hadid, hasModeledFor, Givenchy]
-
A.
Givenchy
chosen
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.
-
B.
Chanel
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.
-
C.
Chloé
Chloé is a central heroine of the ancient Greek pastoral romance "Daphnis and Chloé," known for her innocent love story with the shepherd Daphnis.
-
D.
Chloé
Chloé is a French luxury fashion house renowned for its feminine ready-to-wear, leather goods, and accessories.
-
E.
Dior
Dior is a renowned French luxury fashion house celebrated worldwide for its haute couture, ready-to-wear, accessories, and iconic fragrances.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66438633481908710907c48806499 |
completed | April 20, 2026, 5:36 p.m. |
Created at: April 11, 2026, 3:40 p.m.