Triple
T20016167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asurini do Xingu |
E494722
|
entity |
| Predicate | bodyPaintingMotifs |
P51314
|
FINISHED |
| Object | geometric motifs |
—
|
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: geometric motifs | Statement: [Asurini do Xingu, bodyPaintingMotifs, geometric motifs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bodyPaintingMotifs Context triple: [Asurini do Xingu, bodyPaintingMotifs, geometric motifs]
-
A.
traditionalMotif
chosen
Indicates that something incorporates, represents, or is characterized by a motif rooted in established cultural or historical traditions.
-
B.
artisticTheme
Indicates the central artistic subject, concept, or motif that characterizes or is expressed by a creative work.
-
C.
visualDesignInspiredBy
Indicates that the visual design of one entity is influenced, modeled, or derived from the visual style or appearance of another entity.
-
D.
paintingTradition
Indicates a stylistic or cultural school of painting to which an artwork or artist belongs.
-
E.
facialMarkings
Indicates that one entity has distinctive marks, patterns, or features on its face in relation to another entity or context.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6623cb8188190b95913ffed895930 |
completed | April 20, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69e54cdddbd48190becc8b2aa5ab4ef9 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:34 p.m.