Triple
T26364641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Topeng Betawi |
E660298
|
entity |
| Predicate | maskStyle |
P160457
|
FINISHED |
| Object | character-specific masks |
—
|
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: character-specific masks | Statement: [Topeng Betawi, maskStyle, character-specific masks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maskStyle Context triple: [Topeng Betawi, maskStyle, character-specific masks]
-
A.
maskStyle
chosen
Indicates the style or design characteristics of a mask used or worn in the described context.
-
B.
maskPattern
Indicates a relationship where one entity serves as a masking template or pattern that determines which parts or aspects of another entity are revealed, hidden, or transformed.
-
C.
maskColor
Indicates the color attribute associated with a mask.
-
D.
mask
Indicates that one entity covers, conceals, or obscures another entity, typically to hide its identity, appearance, or specific features.
-
E.
marginStyle
Indicates how the margins around an element are styled or configured in relation to surrounding content.
- 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_69ee8126d52c8190bc0b34337c2c9aa8 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f6102b07fc81908c14c1bcca28c1b0 |
completed | May 2, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69f602d2ec748190ae95154f34c7878f |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 26, 2026, 10:54 p.m.