Triple
T3428429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LVMH |
E72279
|
entity |
| Predicate | hasDivision |
P35
|
FINISHED |
| Object |
Fashion and Leather Goods
Fashion and Leather Goods is a core LVMH business segment encompassing its luxury fashion houses and high-end leather accessories brands.
|
E356409
|
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: Fashion and Leather Goods | Statement: [LVMH, hasDivision, Fashion and Leather Goods]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fashion and Leather Goods Context triple: [LVMH, hasDivision, Fashion and Leather Goods]
-
A.
Nike accessories
Nike accessories are branded athletic and lifestyle items—such as bags, hats, socks, and gear—produced by Nike and typically featuring the iconic Swoosh logo.
-
B.
Fashion Group
Fashion Group is the fashion and apparel business division of Samsung C&T, overseeing the company’s clothing and lifestyle brands.
-
C.
Boots
Boots is an American singer, songwriter, and record producer best known for his influential work on Beyoncé’s self-titled 2013 album.
-
D.
Boots
Boots is a major British pharmacy-led health and beauty retailer and pharmacy chain with stores across the United Kingdom and other countries.
-
E.
Sneakers
"Sneakers" is a 1992 comedic heist thriller film about a team of security experts who become entangled in espionage over a powerful code-breaking device.
- 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: Fashion and Leather Goods Triple: [LVMH, hasDivision, Fashion and Leather Goods]
Generated description
Fashion and Leather Goods is a core LVMH business segment encompassing its luxury fashion houses and high-end leather accessories brands.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fashion and Leather Goods Target entity description: Fashion and Leather Goods is a core LVMH business segment encompassing its luxury fashion houses and high-end leather accessories brands.
-
A.
Nike accessories
Nike accessories are branded athletic and lifestyle items—such as bags, hats, socks, and gear—produced by Nike and typically featuring the iconic Swoosh logo.
-
B.
Fashion Group
Fashion Group is the fashion and apparel business division of Samsung C&T, overseeing the company’s clothing and lifestyle brands.
-
C.
Boots
Boots is an American singer, songwriter, and record producer best known for his influential work on Beyoncé’s self-titled 2013 album.
-
D.
Boots
Boots is a major British pharmacy-led health and beauty retailer and pharmacy chain with stores across the United Kingdom and other countries.
-
E.
Sneakers
"Sneakers" is a 1992 comedic heist thriller film about a team of security experts who become entangled in espionage over a powerful code-breaking device.
- 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_69ad85ae14308190bcbc25cfa0246c0b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb983f4608190abcc27aa7b926deb |
completed | March 8, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b35478448481908e1c0f717d99f992 |
completed | March 13, 2026, 12:04 a.m. |
| NEDg | Description generation | batch_69b35546dfa0819081800009fbe8afe3 |
completed | March 13, 2026, 12:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b355cecc4c81908ecb5f83e89b4a00 |
completed | March 13, 2026, 12:09 a.m. |
Created at: March 8, 2026, 3:15 p.m.