Triple
T1816974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Kors |
E40456
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Michael Kors |
E40456
|
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: Michael Kors | Statement: [Michael Kors, name, Michael Kors]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Kors Context triple: [Michael Kors, name, Michael Kors]
-
A.
Michael Kors
chosen
Michael Kors is an American fashion designer best known for his eponymous luxury brand specializing in ready-to-wear clothing, accessories, and handbags.
-
B.
Nicole Miller
Nicole Miller is an American fashion designer renowned for her modern, feminine womenswear and bold use of color and print.
-
C.
Michele Lacroix
Michele Lacroix is a Belgian public figure best known as the wife of professional footballer Kevin De Bruyne.
-
D.
Carolina Herrera
Carolina Herrera is a Venezuelan-American fashion designer renowned for her elegant, sophisticated clothing and fragrance lines favored by celebrities and socialites.
-
E.
Tommy Hilfiger
Tommy Hilfiger is an American fashion brand and designer known for his classic, preppy clothing and accessories that blend traditional Americana with modern style.
- 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_69a8864526c081908a3a4d74f689e2c5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa65f7b84081909005ce36ef1199db |
completed | March 6, 2026, 5:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adbf6019bc81909266b7f03b282f34 |
completed | March 8, 2026, 6:26 p.m. |
Created at: March 4, 2026, 7:32 p.m.