Triple
T16056570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KNB EFX Group |
E389495
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | makeup effects studio |
C33731
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: makeup effects studio Context triple: [KNB EFX Group, instanceOf, makeup effects studio]
-
A.
makeup effects company
chosen
A makeup effects company is a business that designs, creates, and applies specialized cosmetic and prosthetic effects for film, television, theater, and other visual media productions.
-
B.
special effects studio
A special effects studio is a creative production facility that designs, develops, and implements visual and practical effects for film, television, games, and other media to enhance or simulate on-screen realities.
-
C.
special effects studio
A special effects studio is a creative production facility that designs, develops, and executes visual and practical effects for film, television, games, and other media to enhance or transform on-screen imagery.
-
D.
special effects makeup artist
A special effects makeup artist is a professional who designs and applies prosthetics, cosmetics, and other materials to transform performers’ appearances for film, television, theater, and live events, often creating realistic injuries, creatures, or fantastical characters.
-
E.
makeup artist
A makeup artist is a professional who applies cosmetics and related products to enhance, transform, or create specific looks for clients in contexts such as fashion, film, theater, photography, and personal events.
- F. None of above.
Provenance (1 batch)
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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
Created at: April 10, 2026, 4:56 a.m.