Triple
T6901113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | René Lacoste |
E159494
|
entity |
| Predicate | founded |
P104
|
FINISHED |
| Object | Lacoste |
E386135
|
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: Lacoste | Statement: [René Lacoste, founded, Lacoste]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lacoste Context triple: [René Lacoste, founded, Lacoste]
-
A.
Lacoste
chosen
Lacoste is a French clothing company best known for its crocodile-logo polo shirts and sportswear.
-
B.
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.
-
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.
Loewe
Loewe is a Spanish luxury fashion house renowned for its high-end leather goods, ready-to-wear, and accessories.
-
E.
Hugo Boss
Hugo Boss is a German luxury fashion house known for its high-end menswear, fragrances, and accessories.
- 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_69c6883822e0819091e321526f20ae0a |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9603f448190bb9f963c17ca206d |
completed | March 27, 2026, 7:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7512268ec81908e2f751a585cb8da |
completed | March 28, 2026, 3:55 a.m. |
Created at: March 27, 2026, 2:24 p.m.