Triple
T21633324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cuban League |
E533889
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Havana |
—
|
NE NERFINISHED |
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: Havana | Statement: [Cuban League, location, Havana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Havana Context triple: [Cuban League, location, Havana]
-
A.
Havana
"Havana" is a Latin-influenced pop song by Cuban-American singer Camila Cabello that became an international hit and one of her signature tracks.
-
B.
Habana
Habana is the surname of Bryan Habana, the renowned South African rugby union winger considered one of the greatest try-scorers in the sport’s history.
-
C.
Habana
Habana was the original name of the Confederate ironclad warship later known as CSS Sumter, active during the American Civil War.
-
D.
Habana
"Habana" is a Latin jazz album by American trumpeter Roy Hargrove, blending Afro-Cuban rhythms with contemporary jazz.
-
E.
Havana, Cuba
chosen
Havana, Cuba is the capital and largest city of Cuba, renowned for its historic architecture, vibrant culture, and significant political and economic role in the Caribbean.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c465ae7481908577b7209fdb2a77 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef52185dbc819096ad2fc5b7d953f8 |
completed | April 27, 2026, 12:10 p.m. |
Created at: April 16, 2026, 6:35 p.m.