Triple
T390036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serenade |
E8859
|
entity |
| Predicate | iconicImage |
P8270
|
FINISHED |
| Object | opening tableau of women in blue tulle |
—
|
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: opening tableau of women in blue tulle | Statement: [Serenade, iconicImage, opening tableau of women in blue tulle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: iconicImage Context triple: [Serenade, iconicImage, opening tableau of women in blue tulle]
-
A.
iconographyFeature
chosen
Indicates a visual element or motif that appears as a distinct feature within a work’s iconography.
-
B.
logoImage
Indicates the image that serves as the logo representing an entity.
-
C.
brandImage
Indicates the perceived overall impression, reputation, and associations that people hold about a particular brand.
-
D.
notableCultImage
Indicates that an entity is associated with a significant or historically important religious or cultic image.
-
E.
obverseDepiction
Indicates that one entity is depicted on the obverse (front) side of another, such as the front face of a coin or medal.
- 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_69a2e7f55c60819097aff65ea2ca2832 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec5bdc848190826701590070497b |
completed | Feb. 28, 2026, 1:23 p.m. |
| PD | Predicate disambiguation | batch_69a2e96960608190bdd342da9c5ddb5e |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.