Triple
T22717863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PPR |
E561781
|
entity |
| Predicate | owns |
P347
|
FINISHED |
| Object | Stella McCartney |
—
|
NE NERFINISHED |
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: Stella McCartney | Statement: [PPR, owns, Stella McCartney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stella McCartney Context triple: [PPR, owns, Stella McCartney]
-
A.
Stella McCartney
chosen
Stella McCartney is a British fashion designer renowned for her sustainable, animal-free luxury clothing and accessories.
-
B.
Lea McCartney
Lea McCartney is known as the sister of American singer and actor Jesse McCartney.
-
C.
Jill Stuart
Jill Stuart is an American fashion designer known for her contemporary, feminine clothing and accessories label popular on international runways.
-
D.
Isabel Marant
Isabel Marant is a French fashion designer known for her effortlessly chic, bohemian-inspired ready-to-wear collections and influential Parisian label.
-
E.
Vivienne Westwood
Vivienne Westwood was a pioneering British fashion designer known for shaping punk and new wave style and for her provocative, politically charged designs.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454fc984819088213b58ee87a002 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1790ecbc48190926d16b20b674dbd |
completed | April 29, 2026, 3:20 a.m. |
Created at: April 17, 2026, 3:19 p.m.