Triple
T7274315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Málaga Airport |
E162985
|
entity |
| Predicate | cityServed |
P82
|
FINISHED |
| Object | Torremolinos |
E491107
|
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: Torremolinos | Statement: [Málaga Airport, cityServed, Torremolinos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Torremolinos Context triple: [Málaga Airport, cityServed, Torremolinos]
-
A.
Estepona
Estepona is a coastal resort town on Spain’s Costa del Sol, known for its Mediterranean beaches, marina, and whitewashed old town.
-
B.
Marbella
Marbella is a popular resort city on Spain’s Costa del Sol, known for its Mediterranean beaches, luxury marinas, upscale nightlife, and historic old town.
-
C.
Tarifa
Tarifa is a coastal town in southern Spain known as the southernmost point of mainland Europe and a major destination for wind sports like kitesurfing and windsurfing.
-
D.
Salobreña
Salobreña is a picturesque coastal town on Spain’s Costa Tropical, known for its whitewashed hillside houses and hilltop Moorish castle overlooking the Mediterranean Sea.
-
E.
Torremolinos, Spain
chosen
Torremolinos, Spain is a popular resort town on the Costa del Sol known for its Mediterranean beaches, vibrant nightlife, and tourism-focused economy.
- 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_69c6885c5964819085b209701769877f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb0de9f48190807dd148758bad62 |
completed | March 27, 2026, 8:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7fa6d84b88190916b1d9ddb0d1d0d |
completed | March 28, 2026, 3:57 p.m. |
Created at: March 27, 2026, 2:58 p.m.