Triple
T14672738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borbona |
E344552
|
entity |
| Predicate | hasTraditionalLocalCulture |
P3114
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Borbona, hasTraditionalLocalCulture, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalLocalCulture Context triple: [Borbona, hasTraditionalLocalCulture, true]
-
A.
hasMulticulturalTradition
Indicates that an entity possesses customs, practices, or heritage derived from or influenced by multiple cultural backgrounds.
-
B.
hasCulturalLegacyIn
Indicates that an entity has left a lasting cultural influence, impact, or heritage within a particular place, community, or cultural context.
-
C.
hasTraditionalCulturalSites
Indicates that an entity possesses or is associated with locations recognized for their traditional or culturally significant heritage.
-
D.
hasDistinctCulturalHeritage
Indicates that an entity possesses a unique cultural background, traditions, or practices that distinguish it from other entities.
-
E.
hasCulturalFeature
chosen
Indicates that an entity possesses, includes, or is characterized by a particular cultural element, attribute, or landmark.
- 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb55064cc8190b9669d0b2da61825 |
completed | April 14, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69de6576f0208190aa94d995e797ac38 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:27 a.m.