Triple
T21751963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean Marie Farina |
E536936
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Roger & Gallet |
—
|
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: Roger & Gallet | Statement: [Jean Marie Farina, producer, Roger & Gallet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roger & Gallet Context triple: [Jean Marie Farina, producer, Roger & Gallet]
-
A.
Roger&Gallet
chosen
Roger & Gallet is a historic French perfume and skincare brand known for its luxurious fragrances, soaps, and body care products.
-
B.
Lacroix
Lacroix is a French surname borne by various notable individuals across fields such as sports, fashion, and the arts.
-
C.
Galliano
Galliano is a high-fashion brand led by British designer John Galliano, known for its theatrical, avant-garde couture and dramatic runway presentations.
-
D.
Denis of Paris
Denis of Paris is a 3rd-century Christian martyr and bishop, venerated as the patron saint of Paris and traditionally regarded as one of the city’s earliest evangelizers.
-
E.
Petit & Fritsen
Petit & Fritsen is a historic Dutch bell foundry renowned for casting church bells and carillons used in notable towers and monuments worldwide.
- 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_69e0c46eab808190b848242d63a17c47 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01d8a6d4881908cc69e7247cce3a5 |
completed | April 28, 2026, 2:38 a.m. |
Created at: April 16, 2026, 6:50 p.m.