Triple
T2192599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coat of arms of Groningen (province) |
E49895
|
entity |
| Predicate | hasVisualMotif |
P31989
|
FINISHED |
| Object | imperial eagle |
—
|
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: imperial eagle | Statement: [Coat of arms of Groningen (province), hasVisualMotif, imperial eagle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVisualMotif Context triple: [Coat of arms of Groningen (province), hasVisualMotif, imperial eagle]
-
A.
hasVisualIndicator
Indicates that an entity is associated with some form of visual cue or marker that signals its status, condition, or presence.
-
B.
usesMotifsFrom
chosen
Indicates that one entity incorporates or draws upon recurring themes, patterns, or elements that originate from another entity.
-
C.
containsVisionOf
Indicates that one entity includes, depicts, or embodies a visual representation or image of another entity.
-
D.
hasSignatureVisualStyle
Indicates that an entity is characterized by a distinctive and recognizable visual style that sets it apart from others.
-
E.
hasVisionOf
Indicates that one entity perceives, imagines, or foresees another entity or scenario, typically in a mental, prophetic, or visualized form.
- 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_69a88aaba3c48190b351cab9b26989ff |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf48ceb48190956df39377df0548 |
completed | March 7, 2026, 6:01 a.m. |
| PD | Predicate disambiguation | batch_69abbda52328819089c7ab111bebb0ca |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.