Triple
T4959934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swedavia |
E111378
|
entity |
| Predicate | owns |
P347
|
FINISHED |
| Object |
Umeå Airport
Umeå Airport is a regional airport in northern Sweden serving the city of Umeå with domestic and limited international flights.
|
E523677
|
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: Umeå Airport | Statement: [Swedavia, owns, Umeå Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Umeå Airport Context triple: [Swedavia, owns, Umeå Airport]
-
A.
Luleå Airport
Luleå Airport is a major civilian and military airport in northern Sweden serving the city of Luleå and the wider Norrbotten region.
-
B.
Jönköping Airport
Jönköping Airport is a regional airport in southern Sweden serving the city of Jönköping with domestic and limited international flights.
-
C.
Torslanda Airport
Torslanda Airport was the former main airport serving Gothenburg, Sweden, before being superseded by Gothenburg Landvetter Airport.
-
D.
Linköping City Airport
Linköping City Airport is a regional airport in Linköping, Sweden, serving both commercial passenger flights and general aviation.
-
E.
Gustaf III Airport
Gustaf III Airport is the small, short-runway airport serving the Caribbean island of Saint Barthélemy, known for its challenging approach and dramatic landings close to a beach.
- 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: Umeå Airport Triple: [Swedavia, owns, Umeå Airport]
Generated description
Umeå Airport is a regional airport in northern Sweden serving the city of Umeå with domestic and limited international flights.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Umeå Airport Target entity description: Umeå Airport is a regional airport in northern Sweden serving the city of Umeå with domestic and limited international flights.
-
A.
Luleå Airport
Luleå Airport is a major civilian and military airport in northern Sweden serving the city of Luleå and the wider Norrbotten region.
-
B.
Jönköping Airport
Jönköping Airport is a regional airport in southern Sweden serving the city of Jönköping with domestic and limited international flights.
-
C.
Torslanda Airport
Torslanda Airport was the former main airport serving Gothenburg, Sweden, before being superseded by Gothenburg Landvetter Airport.
-
D.
Linköping City Airport
Linköping City Airport is a regional airport in Linköping, Sweden, serving both commercial passenger flights and general aviation.
-
E.
Gustaf III Airport
Gustaf III Airport is the small, short-runway airport serving the Caribbean island of Saint Barthélemy, known for its challenging approach and dramatic landings close to a beach.
- 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_69bd4418390c8190b7e9766a2512ce55 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd71da80008190a0d606d5091822b8 |
completed | March 20, 2026, 4:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf6c27ce8c81908253c7639207fd3c |
completed | March 22, 2026, 4:12 a.m. |
| NEDg | Description generation | batch_69bf6ca445fc8190bad2b7be4ff03d18 |
completed | March 22, 2026, 4:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf6d16d93881908099725423926c1d |
completed | March 22, 2026, 4:16 a.m. |
Created at: March 20, 2026, 1:32 p.m.