Triple
T6790661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Permira |
E155921
|
entity |
| Predicate | notableInvestment |
P3488
|
FINISHED |
| Object | Hugo Boss |
E307823
|
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: Hugo Boss | Statement: [Permira, notableInvestment, Hugo Boss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hugo Boss Context triple: [Permira, notableInvestment, Hugo Boss]
-
A.
Hugo Boss
chosen
Hugo Boss is a German luxury fashion house known for its high-end menswear, fragrances, and accessories.
-
B.
Loewe
Loewe is a Spanish luxury fashion house renowned for its high-end leather goods, ready-to-wear, and accessories.
-
C.
Kering
Kering is a French multinational luxury group that owns and manages high-end fashion and leather goods brands such as Gucci, Saint Laurent, and Bottega Veneta.
-
D.
Burberry
Burberry is a British luxury fashion house renowned for its iconic trench coats, distinctive check pattern, and heritage-inspired apparel and accessories.
-
E.
Kenzo
Kenzo is a Japanese masculine given name borne by various notable figures in fields such as architecture, fashion, and entertainment.
- 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_69c6881770fc8190972b2906390380f5 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2acbfc0819081f2d6cebfb91765 |
completed | March 27, 2026, 6:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c71a8c445c8190abea97a04d648f52 |
completed | March 28, 2026, 12:02 a.m. |
Created at: March 27, 2026, 2:15 p.m.