Triple
T21967687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kapelle-Biezelinge railway station |
E542501
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Kapelle |
—
|
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: Kapelle | Statement: [Kapelle-Biezelinge railway station, locatedIn, Kapelle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kapelle Context triple: [Kapelle-Biezelinge railway station, locatedIn, Kapelle]
-
A.
Kapelle
chosen
Kapelle is a small municipality and town in the Dutch province of Zeeland, known for its agricultural landscape and historic village character.
-
B.
Kapellen
Kapellen is a municipality in the Belgian province of Antwerp, known for its residential character and green surroundings.
-
C.
Kapela
Kapela is a mountain range in central Croatia that forms part of the Dinaric Alps and serves as a natural barrier between the continental and coastal regions.
-
D.
Ramskapelle
Ramskapelle is a village in the municipality of Knokke-Heist in West Flanders, Belgium, known for its rural character and historical charm.
-
E.
Kappeln
Kappeln is a small town in northern Germany known for its picturesque harbor on the Schlei inlet and its traditional herring fishery.
- 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_69e0c47fab1081908dc74a6545dbb051 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1245c5d148190af2a06190ba32feb |
completed | April 28, 2026, 9:19 p.m. |
Created at: April 16, 2026, 8:02 p.m.