Triple
T21028221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Islam Khodja Minaret |
E517995
|
entity |
| Predicate | decorativePattern |
P86416
|
FINISHED |
| Object | geometric motifs |
—
|
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: geometric motifs | Statement: [Islam Khodja Minaret, decorativePattern, geometric motifs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: decorativePattern Context triple: [Islam Khodja Minaret, decorativePattern, geometric motifs]
-
A.
decorativeProgram
Indicates a relationship where a program or plan is created or used primarily for decorative, aesthetic, or ornamental purposes rather than functional ones.
-
B.
decorativeComplexity
Indicates the degree or richness of ornamental detail or embellishment present in something.
-
C.
airingPattern
Indicates the recurring schedule or pattern according to which something (such as a program or content) is broadcast or made available.
-
D.
decorationShape
Indicates the geometric or visual form that a decorative element or ornament takes in relation to the object it adorns.
-
E.
ornamentationStyle
chosen
Indicates the decorative design or stylistic approach applied as ornamentation to an 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_69e0b503275c8190afd9a163f997c709 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc7efda081909a4de1c389166bf2 |
completed | April 21, 2026, 4:26 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf274ac81909bbf245627dc8fdc |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 1:55 p.m.