Triple
T519422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen of Heaven |
E10779
|
entity |
| Predicate | iconographyShows |
P8270
|
FINISHED |
| Object | Mary crowned in heaven |
—
|
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: Mary crowned in heaven | Statement: [Queen of Heaven, iconographyShows, Mary crowned in heaven]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: iconographyShows Context triple: [Queen of Heaven, iconographyShows, Mary crowned in heaven]
-
A.
iconographyFeature
chosen
Indicates a visual element or motif that appears as a distinct feature within a work’s iconography.
-
B.
hasIconographicTradition
Indicates that an entity is associated with a recognized, recurring set of visual motifs or symbolic representations within a particular artistic or cultural tradition.
-
C.
depictionType
Indicates the specific manner or style in which something is visually represented or depicted.
-
D.
numberOfFiguresDepicted
Indicates the total count of distinct figures shown within a given depiction or representation.
-
E.
hasIllustrationsBy
Indicates that one entity (such as a work or publication) includes illustrations that were created by another entity (the illustrator).
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1a00a6c8190a62dc7c901c2f2ff |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f016ba5c81909825b04e7525b4ab |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.