Triple
T14373351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fashion and Leather Goods |
E356409
|
entity |
| Predicate | ownsBrand |
P1500
|
FINISHED |
| Object | Berluti |
E356398
|
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: Berluti | Statement: [Fashion and Leather Goods, ownsBrand, Berluti]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Berluti Context triple: [Fashion and Leather Goods, ownsBrand, Berluti]
-
A.
Berluti
chosen
Berluti is a French luxury brand renowned for its high-end men's shoes, leather goods, and bespoke tailoring.
-
B.
Loewe
Loewe is a Spanish luxury fashion house renowned for its high-end leather goods, ready-to-wear, and accessories.
-
C.
Fendi
Fendi is a renowned Italian luxury fashion house known for its high-end clothing, leather goods, and iconic handbags.
-
D.
Bottega Veneta
Bottega Veneta is an Italian luxury fashion house renowned for its understated elegance and signature intrecciato leather craftsmanship.
-
E.
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.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9007184c8190aebb003cb6548cc8 |
completed | April 14, 2026, 7:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd551002948190aeb93d245e1449a7 |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:15 a.m.