Triple
T19663365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danza de los Viejitos |
E472138
|
entity |
| Predicate | maskDepicts |
P118298
|
FINISHED |
| Object | wrinkled elderly face |
—
|
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: wrinkled elderly face | Statement: [Danza de los Viejitos, maskDepicts, wrinkled elderly face]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maskDepicts Context triple: [Danza de los Viejitos, maskDepicts, wrinkled elderly face]
-
A.
mask
Indicates that one entity covers, conceals, or obscures another entity, typically to hide its identity, appearance, or specific features.
-
B.
maskColor
Indicates the color attribute associated with a mask.
-
C.
imageDepictedIn
Indicates that a particular image is shown, represented, or included within another resource or context.
-
D.
intendedToDepict
chosen
Indicates that one entity was purposefully created or selected in order to visually represent or portray another entity.
-
E.
typicallyDepicts
Indicates that one entity is most commonly or characteristically portrayed or represented by the other in depictions or images.
- 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_69d8e514f2e08190ba70a4449519d218 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6416671fc81908e25b0477234fa0f |
completed | April 20, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69e514e941008190898d978d7bde91e4 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:45 p.m.