Triple
T15750366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Čičmany |
E381827
|
entity |
| Predicate | hasTraditionalPatternsType |
P120491
|
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: [Čičmany, hasTraditionalPatternsType, geometric motifs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalPatternsType Context triple: [Čičmany, hasTraditionalPatternsType, geometric motifs]
-
A.
hasTraditionalFormIn
Indicates that something possesses a customary or historically established form or representation within a specified context, system, or location.
-
B.
hasTraditionalBase
Indicates that something is supported by, built upon, or derived from an established traditional foundation or practice.
-
C.
hasTraditionalSymbol
Indicates that something is associated with or represented by a conventional or culturally established symbol.
-
D.
isTraditional
Indicates that something adheres to long-established customs, practices, or norms rather than modern or innovative ones.
-
E.
hasUsePattern
Indicates a characteristic or recurring way in which something is typically used or applied.
- F. None of above. chosen
Provenance (4 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0052c6208819098165d61d378d13b |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e0b4d01c9c81909f6b611e8144c838 |
completed | April 16, 2026, 10:07 a.m. |
Created at: April 10, 2026, 4:47 a.m.