Triple
T37907965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ribbon of Saint George |
E945604
|
entity |
| Predicate | visualMotifOf |
P29429
|
FINISHED |
| Object | Russian military commemorative items |
—
|
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: Russian military commemorative items | Statement: [Ribbon of Saint George, visualMotifOf, Russian military commemorative items]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visualMotifOf Context triple: [Ribbon of Saint George, visualMotifOf, Russian military commemorative items]
-
A.
visualCompanion
Indicates that one entity serves as a visual counterpart, partner, or accompanying element to another in a visual context.
-
B.
visualMetaphor
Indicates a relationship where one entity conceptually represents or explains another through a visual analogy or symbolic imagery.
-
C.
visualizedIn
Indicates that something is represented or depicted within a particular visual medium, view, or visualization.
-
D.
visuallyDefines
Indicates that one entity establishes or clarifies the appearance, form, or visual characteristics of another entity.
-
E.
visualElements
chosen
Indicates that one entity contains, uses, or is characterized by specific visual components or graphical features associated with 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_69f76ef20bb0819088b5b6ceecb0b8fc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd166a488190b1bf9316b0790801 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:20 p.m.