Triple
T283313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UNESCO Creative Cities Network |
E5834
|
entity |
| Predicate | hasThematicField |
P6142
|
FINISHED |
| Object | Crafts and Folk Art |
—
|
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: Crafts and Folk Art | Statement: [UNESCO Creative Cities Network, hasThematicField, Crafts and Folk Art]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThematicField Context triple: [UNESCO Creative Cities Network, hasThematicField, Crafts and Folk Art]
-
A.
containsThemeArea
chosen
Indicates that one entity includes or encompasses a specific thematic area as part of its scope or content.
-
B.
hasCentralTheme
Indicates that one entity serves as the primary or dominant theme or subject matter of another entity.
-
C.
hasSubdiscipline
Indicates that one discipline includes another, more specialized field of study as a subordinate branch.
-
D.
hasNotableSubject
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
-
E.
hasLyricalTheme
Indicates that one entity (typically a creative work) features or is characterized by a particular lyrical subject, topic, or theme.
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a25e0d789881908d6a9a8d6a0d4a6c |
completed | Feb. 28, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69a25b795a6c8190944d48e8418e0ccd |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.