Triple
T22265637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tory Burch |
E550342
|
entity |
| Predicate | brandName |
P1500
|
FINISHED |
| Object | Tory Burch |
—
|
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: Tory Burch | Statement: [Tory Burch, brandName, Tory Burch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tory Burch Context triple: [Tory Burch, brandName, Tory Burch]
-
A.
Tory Burch
chosen
Tory Burch is an American fashion designer and businesswoman known for her eponymous lifestyle brand featuring preppy-bohemian clothing, accessories, and footwear.
-
B.
Jill Stuart
Jill Stuart is an American fashion designer known for her contemporary, feminine clothing and accessories label popular on international runways.
-
C.
Jimmy Choo
Jimmy Choo is a luxury fashion brand best known for its high-end designer shoes, handbags, and accessories.
-
D.
Michael Kors
Michael Kors is an American fashion designer best known for his eponymous luxury brand specializing in ready-to-wear clothing, accessories, and handbags.
-
E.
Betsey Johnson
Betsey Johnson is an American fashion designer known for her whimsical, colorful, and exuberant clothing designs and her playful, cartwheeling runway finales.
- 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_69e11e43d8208190aff4f9cf7f2c2a8a |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f141bb850881908f5e9c37afb52ca8 |
completed | April 28, 2026, 11:24 p.m. |
Created at: April 16, 2026, 8:39 p.m.