Triple
T3768644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lacoste Ladies Open de France |
E82741
|
entity |
| Predicate | sponsor |
P67
|
FINISHED |
| Object |
Lacoste
Lacoste is a French clothing company best known for its crocodile-logo polo shirts and sportswear.
|
E386135
|
NE FINISHED |
How this triple was built (4 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: [Lacoste Ladies Open de France, sponsor, Lacoste]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lacoste Context triple: [Lacoste Ladies Open de France, sponsor, Lacoste]
-
A.
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.
-
B.
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.
-
C.
Loewe
Loewe is a Spanish luxury fashion house renowned for its high-end leather goods, ready-to-wear, and accessories.
-
D.
Hugo Boss
Hugo Boss is a German luxury fashion house known for its high-end menswear, fragrances, and accessories.
-
E.
Fendi
Fendi is a renowned Italian luxury fashion house known for its high-end clothing, leather goods, and iconic handbags.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lacoste Triple: [Lacoste Ladies Open de France, sponsor, Lacoste]
Generated description
Lacoste is a French clothing company best known for its crocodile-logo polo shirts and sportswear.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lacoste Target entity description: Lacoste is a French clothing company best known for its crocodile-logo polo shirts and sportswear.
-
A.
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.
-
B.
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.
-
C.
Loewe
Loewe is a Spanish luxury fashion house renowned for its high-end leather goods, ready-to-wear, and accessories.
-
D.
Hugo Boss
Hugo Boss is a German luxury fashion house known for its high-end menswear, fragrances, and accessories.
-
E.
Fendi
Fendi is a renowned Italian luxury fashion house known for its high-end clothing, leather goods, and iconic handbags.
- F. None of above. chosen
Provenance (5 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_69ad8b207b0081909d2b48843fbd8795 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc2d4b848190bf63fb3ed5d3b2d9 |
completed | March 8, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e5251d2481909f692937271a8013 |
completed | March 14, 2026, 4:33 a.m. |
| NEDg | Description generation | batch_69b4e73b64388190b1f32a9ec498bf11 |
completed | March 14, 2026, 4:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4e78a5dcc8190b25c9a35728bfb94 |
completed | March 14, 2026, 4:43 a.m. |
Created at: March 8, 2026, 3:35 p.m.