Triple
T1102958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cubana de Aviación |
E25422
|
entity |
| Predicate | callsign |
P1565
|
FINISHED |
| Object |
CUBANA
CUBANA is the radio callsign used by Cubana de Aviación, the national flag carrier airline of Cuba.
|
E127198
|
NE FINISHED |
How this triple was built (4 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: CUBANA | Statement: [Cubana de Aviación, callsign, CUBANA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CUBANA Context triple: [Cubana de Aviación, callsign, CUBANA]
-
A.
Cuba
Cuba is a Caribbean island nation known for its communist government, historic Havana architecture, classic cars, and influential music and culture.
-
B.
Segunda Angostura
Segunda Angostura is a narrow channel within the Strait of Magellan in southern Chile, known for its constricted waters and challenging navigation conditions.
-
C.
Canóvanas
Canóvanas is a municipality in northeastern Puerto Rico known for its proximity to San Juan and its blend of suburban communities with rural, mountainous landscapes.
-
D.
Patria
Patria is a Finnish defense industry company known for developing and manufacturing military vehicles, systems, and related defense solutions.
-
E.
Castro Marim
Castro Marim is a town and municipality in Portugal’s Algarve region, near the Spanish border, known for its historic castle and salt marshes.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: CUBANA Triple: [Cubana de Aviación, callsign, CUBANA]
Generated description
CUBANA is the radio callsign used by Cubana de Aviación, the national flag carrier airline of Cuba.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CUBANA Target entity description: CUBANA is the radio callsign used by Cubana de Aviación, the national flag carrier airline of Cuba.
-
A.
Cuba
Cuba is a Caribbean island nation known for its communist government, historic Havana architecture, classic cars, and influential music and culture.
-
B.
Segunda Angostura
Segunda Angostura is a narrow channel within the Strait of Magellan in southern Chile, known for its constricted waters and challenging navigation conditions.
-
C.
Canóvanas
Canóvanas is a municipality in northeastern Puerto Rico known for its proximity to San Juan and its blend of suburban communities with rural, mountainous landscapes.
-
D.
Patria
Patria is a Finnish defense industry company known for developing and manufacturing military vehicles, systems, and related defense solutions.
-
E.
Castro Marim
Castro Marim is a town and municipality in Portugal’s Algarve region, near the Spanish border, known for its historic castle and salt marshes.
- F. None of above. chosen
Provenance (5 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_69a49428d4448190b3b36991ceae87ce |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9c375848190baec4d534f489616 |
completed | March 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4c47dbf88190a1898d7bda32ecb2 |
completed | March 7, 2026, 4:03 p.m. |
| NEDg | Description generation | batch_69ac4feb86c88190abaed60e0782fec6 |
completed | March 7, 2026, 4:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac509b6fe48190973bbfabdc976541 |
completed | March 7, 2026, 4:21 p.m. |
Created at: March 1, 2026, 7:43 p.m.