Triple
T13184738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanity Fair Brands |
E313817
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | Vassarette |
E1026758
|
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: Vassarette | Statement: [Vanity Fair Brands, hasBrand, Vassarette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vassarette Context triple: [Vanity Fair Brands, hasBrand, Vassarette]
-
A.
Vassarette
chosen
Vassarette is a lingerie and intimate apparel brand known for its affordable bras, panties, and shapewear sold primarily in mass-market retail channels.
-
B.
Vallon
Vallon is a small municipality in the canton of Fribourg in western Switzerland.
-
C.
Vallon
Vallon is the surname of Priest Vallon, a fictional Irish-American gang leader and father of Amsterdam Vallon in the film "Gangs of New York."
-
D.
Verchota
Verchota is a surname most notably associated with Phil Verchota, an American ice hockey player and member of the 1980 "Miracle on Ice" U.S. Olympic team.
-
E.
Valleiry
Valleiry is a small French commune in the Haute-Savoie department of the Auvergne-Rhône-Alpes region in southeastern France, near the Swiss border.
- 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_69d806ae1e08819090d95bfe1538cc17 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c4a0b0081908027bf77442ff5ff |
completed | April 10, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff1581388190824a5377b64bd0ef |
completed | May 3, 2026, 7:53 a.m. |
Created at: April 9, 2026, 9:15 p.m.