Triple
T10072681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salasaca people |
E213667
|
entity |
| Predicate | textileStyle |
P64189
|
FINISHED |
| Object | geometric patterns |
—
|
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 patterns | Statement: [Salasaca people, textileStyle, geometric patterns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textileStyle Context triple: [Salasaca people, textileStyle, geometric patterns]
-
A.
textileType
Indicates the specific kind or category of textile material associated with an entity.
-
B.
textileFeature
chosen
Indicates a characteristic, property, or notable aspect associated with a textile or fabric.
-
C.
fashionStyle
Indicates the characteristic way in which an entity dresses or presents themselves in terms of clothing and appearance.
-
D.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
E.
stylingTool
Indicates a tool or instrument used to style, shape, or arrange something (typically hair, clothing, or design elements).
- 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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd013c9d0819091ebe6fc399832de |
completed | April 2, 2026, 2:10 a.m. |
| PD | Predicate disambiguation | batch_69cd4b97870481908f7a89df10d58a9e |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 8:59 p.m.