Triple
T7348599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fatimid art |
E169438
|
entity |
| Predicate | characteristicMotif |
P41002
|
FINISHED |
| Object | vegetal arabesques |
—
|
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: vegetal arabesques | Statement: [Fatimid art, characteristicMotif, vegetal arabesques]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characteristicMotif Context triple: [Fatimid art, characteristicMotif, vegetal arabesques]
-
A.
featuresMotif
chosen
Indicates that something contains, incorporates, or prominently includes a particular recurring motif or pattern.
-
B.
primaryMotif
Indicates that one entity serves as the main recurring theme or dominant motif associated with another entity.
-
C.
characterizedBy
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
D.
usesMotifsFrom
Indicates that one entity incorporates or draws upon recurring themes, patterns, or elements that originate from another entity.
-
E.
findingCharacterization
Indicates that a finding is being described or classified in terms of its nature, features, or diagnostic significance.
- 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_69c68a5878888190968ce4d04db8d69f |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f139505c8190a7158cf59a6e089e |
completed | March 27, 2026, 9:06 p.m. |
| PD | Predicate disambiguation | batch_69c6f02aeeb8819099d1626566cec18b |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:05 p.m.