Triple
T17479269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boy A |
E425614
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Cuba Pictures |
—
|
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: Cuba Pictures | Statement: [Boy A, productionCompany, Cuba Pictures]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cuba Pictures Context triple: [Boy A, productionCompany, Cuba Pictures]
-
A.
Cuba Pictures
chosen
Cuba Pictures is a British film and television production company known for producing high-quality, often literary-based dramas and series.
-
B.
Cuba (Capricho)
Cuba (Capricho) is a lively, dance-inspired piano piece by Isaac Albéniz that evokes the rhythms and atmosphere of Cuban music.
-
C.
Town of Cuba
The Town of Cuba is a small rural municipality in southwestern New York State known for its scenic countryside and proximity to Cuba Lake.
-
D.
Central Cuba
Central Cuba is a geographic area on the island of Cuba known for its mix of colonial cities, agricultural plains, and coastal regions along the Atlantic and Caribbean.
-
E.
CUBANA
CUBANA is the radio callsign used by Cubana de Aviación, the national flag carrier airline of Cuba.
- 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_69d889dbc2e88190b18ea6115e819258 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451be5fd08190aeaa12b3a6d6c6d4 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:48 a.m.