Triple
T17529425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portraits of Federico da Montefeltro and Battista Sforza |
E426889
|
entity |
| Predicate | depictsLandscape |
P1581
|
FINISHED |
| Object | idealized hilly countryside |
—
|
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: idealized hilly countryside | Statement: [Portraits of Federico da Montefeltro and Battista Sforza, depictsLandscape, idealized hilly countryside]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsLandscape Context triple: [Portraits of Federico da Montefeltro and Battista Sforza, depictsLandscape, idealized hilly countryside]
-
A.
hasLandscapeFeatures
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
B.
landscapeStyle
Indicates the design style or aesthetic approach applied to a landscape or outdoor environment.
-
C.
isPartOfScenicVista
Indicates that something is included within, or contributes to, a larger scenic vista or panoramic view.
-
D.
landscapeAbstraction
Indicates that one entity is an abstract or non-literal representation derived from the landscape or its features.
-
E.
depicts
chosen
Indicates that one entity visually represents, portrays, or shows 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e45367d68c819097f300381322f11d |
completed | April 19, 2026, 4 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f8b9888190aa8a45e09acf4319 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:49 a.m.