Triple
T21319066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronneby Airport |
E525560
|
entity |
| Predicate | servesRegion |
P82
|
FINISHED |
| Object | Blekinge |
—
|
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: Blekinge | Statement: [Ronneby Airport, servesRegion, Blekinge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blekinge Context triple: [Ronneby Airport, servesRegion, Blekinge]
-
A.
Blekinge
chosen
Blekinge is a historical province in southern Sweden on the Baltic Sea coast, known for its archipelago, maritime heritage, and strategic location.
-
B.
Östergötland County
Östergötland County is an administrative region in southeastern Sweden known for its mix of historic cities, fertile plains, and coastal and archipelago landscapes along the Baltic Sea.
-
C.
Södermanland
Södermanland is a historical province in eastern Sweden, located south of Lake Mälaren and west of the Baltic Sea, known for its castles, lakes, and early Swedish cultural heritage.
-
D.
Kalmar län
Kalmar län is a county in southeastern Sweden known for its Baltic Sea coastline, historic towns, and the island of Öland.
-
E.
Skåne County
Skåne County is Sweden’s southernmost county, known for its fertile farmland, coastal landscapes, and major cities such as Malmö and Lund.
- 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_69e0b51ad810819098c12392c8e55f6c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e77ecf12248190bb4172ad7416775e |
completed | April 21, 2026, 1:42 p.m. |
Created at: April 16, 2026, 4:38 p.m.