Triple
T20379028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Crucifixion (Joachim Wtewael) |
E497769
|
entity |
| Predicate | hasVividDetail |
P132102
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Crucifixion (Joachim Wtewael), hasVividDetail, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVividDetail Context triple: [The Crucifixion (Joachim Wtewael), hasVividDetail, true]
-
A.
visualDetail
chosen
Indicates that one entity provides or specifies the visual characteristics, features, or appearance details of another entity.
-
B.
hasBrightSpots
Indicates that an entity possesses one or more areas or points that are noticeably brighter than their surroundings.
-
C.
hasBrightOrchestrationOrTexture
Indicates that the music exhibits a vivid, clear, or shimmering orchestral sound or instrumental texture.
-
D.
hasVignette
Indicates that one entity possesses, includes, or is associated with a vignette (such as a brief scene, illustration, or decorative element).
-
E.
hasPhotogenicFeature
Indicates that an entity possesses a visual characteristic or attribute that is especially attractive or appealing when photographed.
- 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_69e0b4a5b7908190a972e4e7e698ae94 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678af651c8190b4922294a937e699 |
completed | April 20, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69e57648be3c81908256838228cabf5c |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:27 a.m.