Triple
T10135060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bay Area Figurative painters |
E226833
|
entity |
| Predicate | characteristicStyle |
P20701
|
FINISHED |
| Object | loose brushwork |
—
|
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: loose brushwork | Statement: [Bay Area Figurative painters, characteristicStyle, loose brushwork]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characteristicStyle Context triple: [Bay Area Figurative painters, characteristicStyle, loose brushwork]
-
A.
characterStyle
Indicates how a character is visually or typographically presented, such as its font, weight, size, or decorative attributes.
-
B.
stylingFeature
chosen
Indicates a visual or design-related characteristic applied to an entity, such as formatting, layout, or aesthetic treatment.
-
C.
styleTendsTo
Indicates that one style is generally inclined or likely to develop, appear, or be adopted in the direction of another style.
-
D.
styleSpecialty
Indicates a relationship where an entity’s expertise, focus, or specialization is in a particular style or stylistic approach.
-
E.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
- 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_69ca8433ec308190b8b25a6fe359c34c |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cde87e1f908190a53865420f2b8f93 |
completed | April 2, 2026, 3:54 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba4f5d88190ba68e63be10b08c7 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:06 p.m.