Triple
T15916350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fast Retailing |
E385979
|
entity |
| Predicate | brandPortfolioIncludes |
P18121
|
FINISHED |
| Object | Comptoir des Cotonniers |
E1182346
|
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: Comptoir des Cotonniers | Statement: [Fast Retailing, brandPortfolioIncludes, Comptoir des Cotonniers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Comptoir des Cotonniers Context triple: [Fast Retailing, brandPortfolioIncludes, Comptoir des Cotonniers]
-
A.
Comptoir des Cotonniers
chosen
Comptoir des Cotonniers is a French fashion brand known for its chic, contemporary womenswear and Parisian-inspired style.
-
B.
Groupe Drouot
Groupe Drouot was a French insurance company that later became part of AXA, one of the world’s largest insurance and asset management groups.
-
C.
Les Bouchères
Les Bouchères is a named vineyard climat in the Meursault appellation of Burgundy, France, known for producing high-quality Chardonnay wines.
-
D.
Boucicaut
Boucicaut is a station on the Paris Métro serving the 15th arrondissement of Paris.
-
E.
Marché Poncelet
Marché Poncelet is a traditional open-air food market in Paris known for its high-quality produce, specialty shops, and lively neighborhood atmosphere.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e15662e2c481909e3582be01f05d08 |
completed | April 16, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5a79b808190850fa9d327f7ef72 |
completed | May 9, 2026, 10:31 p.m. |
Created at: April 10, 2026, 4:52 a.m.