Triple
T21319053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronneby Airport |
E525560
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Ronneby |
—
|
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: Ronneby | Statement: [Ronneby Airport, locatedIn, Ronneby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ronneby Context triple: [Ronneby Airport, locatedIn, Ronneby]
-
A.
Ronneby
chosen
Ronneby is a historic town in southern Sweden known for its well-preserved wooden architecture, spa traditions, and scenic location in Blekinge County.
-
B.
Ljungby
Ljungby is a small Swedish town in southern Småland known for its lakeside surroundings, forestry-based economy, and role as a local commercial and cultural center.
-
C.
Stureby
Stureby is a residential district in southern Stockholm, Sweden, known for its suburban character and local amenities.
-
D.
Mjölby
Mjölby is a small Swedish town known for its agricultural surroundings and location in the southern part of Östergötland County.
-
E.
Bollstanäs
Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
- 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.