Triple
T13324693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Air |
E317407
|
entity |
| Predicate | operatedDestination |
P50377
|
FINISHED |
| Object | Larnaca |
E611541
|
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: Larnaca | Statement: [Blue Air, operatedDestination, Larnaca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Larnaca Context triple: [Blue Air, operatedDestination, Larnaca]
-
A.
Larnaca
chosen
Larnaca is a coastal city in southeastern Cyprus known for its historic sites, palm-lined seafront, and role as a major tourism and transport hub.
-
B.
Larnaca District
Larnaca District is an administrative region on the southern coast of Cyprus, known for its historic sites, coastal tourism, and the city of Larnaca as its main urban center.
-
C.
Paphos
Paphos is an ancient coastal city in Cyprus famed in Greek mythology as a principal cult center and legendary birthplace of the goddess Aphrodite.
-
D.
Limassol
Limassol is a major coastal city in Cyprus known for its busy port, tourism, and role as a commercial and financial hub in the Eastern Mediterranean.
-
E.
Limassol District
Limassol District is a coastal administrative region in southern Cyprus that includes the city of Limassol and its surrounding urban and rural areas.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadcd4cb008190af99c4856e76ac08 |
completed | April 11, 2026, 11:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f2cd5688190a2a0db0f0295de83 |
completed | May 3, 2026, 10:10 a.m. |
Created at: April 9, 2026, 9:30 p.m.