Triple
T26364688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ondel-ondel |
E660299
|
entity |
| Predicate | faceDecoration |
P125456
|
FINISHED |
| Object | distinct male and female facial features |
—
|
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: distinct male and female facial features | Statement: [Ondel-ondel, faceDecoration, distinct male and female facial features]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: faceDecoration Context triple: [Ondel-ondel, faceDecoration, distinct male and female facial features]
-
A.
faceType
Indicates the specific shape or structural category of a face that an entity possesses or is characterized by.
-
B.
facialMarkings
chosen
Indicates that one entity has distinctive marks, patterns, or features on its face in relation to another entity or context.
-
C.
eyeDecoration
Indicates the presence, type, or style of decorative elements applied around or on the eyes.
-
D.
hasFace
Indicates that one entity possesses, displays, or is characterized by a face.
-
E.
faceValueType
Indicates the type or category of a financial instrument’s face (nominal) value, such as how that value is defined or represented.
- 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.