Triple
T3755926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uniqlo |
E82045
|
entity |
| Predicate | hasCollaborationWith |
P398
|
FINISHED |
| Object | Marimekko |
E255236
|
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: Marimekko | Statement: [Uniqlo, hasCollaborationWith, Marimekko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marimekko Context triple: [Uniqlo, hasCollaborationWith, Marimekko]
-
A.
Etro
Etro is an Italian luxury fashion house renowned for its vibrant prints, paisley patterns, and eclectic, bohemian-inspired designs.
-
B.
Iittala
chosen
Iittala is a Finnish design brand renowned for its high-quality glassware and timeless Scandinavian tableware and home objects.
-
C.
Missoni
Missoni is an Italian luxury fashion house renowned for its colorful knitwear and distinctive zigzag patterns.
-
D.
Hansnes
Hansnes is a small coastal village in northern Norway that serves as an administrative and ferry hub for the surrounding islands in Troms.
-
E.
Herve
Herve is a municipality in the province of Liège in Wallonia, eastern Belgium, known for its rural landscape and traditional Herve cheese.
- 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_69ad8b1db40081908b61ffa6b78afd4d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb96dd908190b787b112ecd519df |
completed | March 8, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e50bfdb0819097bdfdd38f553ada |
completed | March 14, 2026, 4:33 a.m. |
Created at: March 8, 2026, 3:35 p.m.