Triple
T19879994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norbit |
E477743
|
entity |
| Predicate | featuresProstheticMakeup |
P112130
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [Norbit, featuresProstheticMakeup, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresProstheticMakeup Context triple: [Norbit, featuresProstheticMakeup, true]
-
A.
usesProstheticMakeup
chosen
Indicates that an entity employs artificial makeup effects or appliances to alter appearance, typically for performance or portrayal purposes.
-
B.
usesStageMakeup
Indicates that one entity applies or wears theatrical or stage makeup in relation to another entity or context.
-
C.
hasMakeupEffectsBy
Indicates that the makeup effects for an entity (such as a film or production) are created or supervised by a specified person or team.
-
D.
makeupType
Indicates the specific kind or category of makeup associated with an entity.
-
E.
makeupArtist
Indicates that one entity serves as the makeup artist for another, applying or designing cosmetic looks for that entity.
- F. None of above.
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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658de4b288190a41bee67f570be1e |
completed | April 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:52 p.m.