Triple
T1099830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santiago de Cuba |
E24352
|
entity |
| Predicate | hasEthnicCulturalInfluence |
P1439
|
FINISHED |
| Object | Afro-Cuban |
—
|
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: Afro-Cuban | Statement: [Santiago de Cuba, hasEthnicCulturalInfluence, Afro-Cuban]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEthnicCulturalInfluence Context triple: [Santiago de Cuba, hasEthnicCulturalInfluence, Afro-Cuban]
-
A.
hasCulturalImpact
Indicates that one entity has influenced, shaped, or significantly affected the culture, values, practices, or artistic expressions of another.
-
B.
affectedEthnicGroup
Indicates that a particular ethnic group is impacted or influenced by an event, condition, policy, or action.
-
C.
hasCulturalFeature
Indicates that an entity possesses, includes, or is characterized by a particular cultural element, attribute, or landmark.
-
D.
hasAssociatedCulture
chosen
Indicates that an entity is related to, influenced by, or characterized by a particular culture.
-
E.
ethnicOrigin
Indicates the relationship where an entity is associated with a particular ethnic group or ancestry.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9be92688190838ce35cd67e01f3 |
completed | March 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69a4b745ef3481909a7ce4647c8567b3 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:43 p.m.