Triple
T13184741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanity Fair Brands |
E313817
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | Bestform |
E1026979
|
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: Bestform | Statement: [Vanity Fair Brands, hasBrand, Bestform]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bestform Context triple: [Vanity Fair Brands, hasBrand, Bestform]
-
A.
Bestform
chosen
Bestform is an intimate apparel brand known for offering comfortable, supportive bras and lingerie for everyday wear.
-
B.
Vormsi
Vormsi is a sparsely populated Estonian island in the Baltic Sea known for its coastal landscapes, former Swedish-speaking community, and tranquil rural character.
-
C.
Bestsport
Bestsport is a Czech sports and entertainment management company known for operating major venues and events, including Prague’s O2 Arena.
-
D.
Formmeister
Formmeister is the German term used at the Bauhaus school for the master responsible for teaching and overseeing the artistic and formal aspects of design in a workshop.
-
E.
Formas
Formas is a Swedish government research council that funds research in the areas of environment, agricultural sciences, and spatial planning.
- 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.