Triple
T7410048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tenerife South Airport |
E170976
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | Aena |
E140786
|
NE 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: Aena | Statement: [Tenerife South Airport, operator, Aena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aena Context triple: [Tenerife South Airport, operator, Aena]
-
A.
Aena
chosen
Aena is the Spanish state-owned company that manages and operates the majority of airports in Spain and is one of the world’s largest airport operators by passenger traffic.
-
B.
El Al
El Al is Israel's flag carrier airline, known for its extensive international routes and stringent security measures.
-
C.
Radazul
Radazul is a coastal residential and marina area on the island of Tenerife in Spain’s Canary Islands.
-
D.
Iberia Líneas Aéreas de España
Iberia Líneas Aéreas de España is the flag carrier airline of Spain, operating an extensive network of domestic and international flights, primarily through its main hub in Madrid.
-
E.
Burgos Airport
Burgos Airport is a regional public airport in Burgos, Spain, providing domestic air services and connecting the city to the national air transport network.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c68a618bdc81908d8018edadecd1a4 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f29d77848190a6170eb25483224f |
completed | March 27, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c81edbbe6481908904d1a1f7cfb20a |
completed | March 28, 2026, 6:32 p.m. |
Created at: March 27, 2026, 3:10 p.m.