Triple
T15215367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fashion Walk of Fame |
E363623
|
entity |
| Predicate | hasPlaqueFor |
P10975
|
FINISHED |
| Object | Vera Wang |
E835880
|
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: Vera Wang | Statement: [Fashion Walk of Fame, hasPlaqueFor, Vera Wang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vera Wang Context triple: [Fashion Walk of Fame, hasPlaqueFor, Vera Wang]
-
A.
Vera Wang
chosen
Vera Wang is an American fashion designer renowned for her luxury bridal gowns and influential eveningwear collections.
-
B.
Cynthia Rowley
Cynthia Rowley is an American fashion designer known for her playful, colorful, and adventurous ready-to-wear and accessories collections.
-
C.
Annette de la Renta
Annette de la Renta is a New York–based socialite and philanthropist known for her prominent role in high society and as the widow of fashion designer Oscar de la Renta.
-
D.
Jason Wu
Jason Wu is a Taiwanese-Canadian fashion designer renowned for his elegant, modern womenswear and for dressing high-profile figures including former U.S. First Lady Michelle Obama.
-
E.
Donna Karan
Donna Karan is an influential American fashion designer best known for founding the DKNY label and redefining modern women’s workwear with her sleek, versatile designs.
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0076e4348819091fa91c1562e7c5c |
completed | April 15, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fedd2f86688190bafdfe72033eda90 |
completed | May 9, 2026, 7:07 a.m. |
Created at: April 10, 2026, 3:11 a.m.