Triple
T1408413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prada |
E31748
|
entity |
| Predicate | brandOwner |
P347
|
FINISHED |
| Object | Prada S.p.A. |
E31748
|
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: Prada S.p.A. | Statement: [Prada, brandOwner, Prada S.p.A.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prada S.p.A. Context triple: [Prada, brandOwner, Prada S.p.A.]
-
A.
Prada
chosen
Prada is a renowned Italian luxury fashion house known for its high-end clothing, leather goods, and accessories.
-
B.
Fendi
Fendi is a renowned Italian luxury fashion house known for its high-end clothing, leather goods, and iconic handbags.
-
C.
Hermès International
Hermès International is a French luxury goods manufacturer renowned for its high-end leather goods, fashion accessories, and ready-to-wear collections.
-
D.
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.
-
E.
Versace
Versace is a renowned Italian luxury fashion house known for its bold, glamorous designs and iconic Medusa logo.
- 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_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3bf7f0c8190aee96818de6ff4a5 |
completed | March 1, 2026, 10:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ace578fe4c8190a4d4ced933fac0b6 |
completed | March 8, 2026, 2:56 a.m. |
Created at: March 1, 2026, 7:59 p.m.