Triple
T6630927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Didymus |
E149920
|
entity |
| Predicate | symbolInChristianArt |
P34702
|
FINISHED |
| Object | spear |
—
|
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: spear | Statement: [Thomas Didymus, symbolInChristianArt, spear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symbolInChristianArt Context triple: [Thomas Didymus, symbolInChristianArt, spear]
-
A.
iconographicSubject
Indicates that one entity serves as the depicted subject or theme represented in the iconography of another entity.
-
B.
iconographyType
Indicates the specific kind or category of visual symbolism or imagery used to represent something.
-
C.
iconographicCategory
Indicates the classification of an entity based on the type or theme of its visual or symbolic representation.
-
D.
emblemSymbolism
chosen
Indicates that one entity serves as an emblem whose design or features symbolically represent or convey meanings about another entity.
-
E.
iconographicSource
Indicates that one entity serves as the visual or symbolic source, model, or reference for the iconography or imagery of 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_69c687ee50048190aa151765bef16193 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c308a08881908501c862b3029321 |
completed | March 27, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c6ad024860819084b9b535b136ede6 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:59 p.m.