Triple
T12984144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | south shore of Lake Vättern |
E321723
|
entity |
| Predicate | hasTransportConnection |
P845
|
FINISHED |
| Object | Jönköping Airport |
E321720
|
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: Jönköping Airport | Statement: [south shore of Lake Vättern, hasTransportConnection, Jönköping Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jönköping Airport Context triple: [south shore of Lake Vättern, hasTransportConnection, Jönköping Airport]
-
A.
Jönköping Airport
chosen
Jönköping Airport is a regional airport in southern Sweden serving the city of Jönköping with domestic and limited international flights.
-
B.
Norrköping Airport
Norrköping Airport is a regional airport in Norrköping, Sweden, serving domestic and limited international flights for the surrounding area.
-
C.
Skövde Airport
Skövde Airport is a small regional airport serving the town of Skövde in Västra Götaland County, Sweden.
-
D.
Linköping City Airport
Linköping City Airport is a regional airport in Linköping, Sweden, serving both commercial passenger flights and general aviation.
-
E.
Uppsala Airport
Uppsala Airport is a Swedish airfield near the city of Uppsala, primarily used for military and general aviation rather than large-scale commercial passenger traffic.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e5e3f208190abd2d4b4d5114834 |
completed | April 10, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c0f95c548190a6fc2c1ea98246c3 |
completed | May 3, 2026, 3:28 a.m. |
Created at: April 9, 2026, 8:40 p.m.