Triple
T13559990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sailboats and Estuary |
E323880
|
entity |
| Predicate | usesBrushwork |
P14919
|
FINISHED |
| Object | dot-like strokes |
—
|
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: dot-like strokes | Statement: [Sailboats and Estuary, usesBrushwork, dot-like strokes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBrushwork Context triple: [Sailboats and Estuary, usesBrushwork, dot-like strokes]
-
A.
usesBrushworkType
chosen
Indicates that an entity employs or is characterized by a particular type or style of brushwork in its creation or execution.
-
B.
brushRepresents
Indicates that one brush or brushstroke is used to symbolically depict, stand in for, or visually represent another object, concept, or element.
-
C.
calligraphicUse
Indicates that one entity uses or applies another entity specifically for calligraphic purposes or in the practice of calligraphy.
-
D.
artUse
Indicates that one entity uses, applies, or employs another entity within an artistic or creative context.
-
E.
hasHandwritingOf
Indicates that one entity’s handwriting style or written text is attributed to, or produced by, another entity.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae13bec4819084c1770638c00ed9 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:47 p.m.