Triple
T29161774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tim Minchin |
E739206
|
entity |
| Predicate | eyeMakeupStyle |
P78811
|
FINISHED |
| Object | heavy eyeliner (stage persona) |
—
|
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: heavy eyeliner (stage persona) | Statement: [Tim Minchin, eyeMakeupStyle, heavy eyeliner (stage persona)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eyeMakeupStyle Context triple: [Tim Minchin, eyeMakeupStyle, heavy eyeliner (stage persona)]
-
A.
eyeDecoration
Indicates the presence, type, or style of decorative elements applied around or on the eyes.
-
B.
eyeType
Indicates the specific kind or category of eyes an entity has, such as their form, structure, or visual style.
-
C.
usesMakeupStyle
Indicates that one entity applies or adopts the makeup style or technique associated with another entity.
-
D.
eyeCharacteristic
Indicates a relationship where an entity possesses a specific attribute, feature, or quality of its eyes.
-
E.
makeupType
chosen
Indicates the specific kind or category of makeup associated with an 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_69f07cb528fc8190a556b73990c347c8 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f662d2056081909eb1b5fdd188816b |
completed | May 2, 2026, 8:47 p.m. |
| PD | Predicate disambiguation | batch_69f65c24f8b48190af81b575f3c15be5 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 11:48 a.m.