Triple
T24254862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Catman |
E603640
|
entity |
| Predicate | wearsMakeupStyle |
P78811
|
FINISHED |
| Object | cat-like face paint |
—
|
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: cat-like face paint | Statement: [The Catman, wearsMakeupStyle, cat-like face paint]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wearsMakeupStyle Context triple: [The Catman, wearsMakeupStyle, cat-like face paint]
-
A.
makeupType
chosen
Indicates the specific kind or category of makeup associated with an entity.
-
B.
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.
-
C.
usesStageMakeup
Indicates that one entity applies or wears theatrical or stage makeup in relation to another entity or context.
-
D.
personHasNotableStyle
Indicates that a person is recognized for having a distinctive or noteworthy style.
-
E.
styledCelebrity
Indicates that one entity (typically a stylist or source) is responsible for selecting or creating the fashion or appearance of a celebrity.
- 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_69e29540da0481909a38bdae315b7a02 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28b8ca4988190b565c2873dc6559d |
completed | April 29, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69f1c450aa508190bc9d372a5f6ee47a |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:05 a.m.