Triple
T9440888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koekelberg |
E227641
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Koekelberg |
E534791
|
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: Koekelberg | Statement: [Koekelberg, capital, Koekelberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koekelberg Context triple: [Koekelberg, capital, Koekelberg]
-
A.
Koekelberg
chosen
Koekelberg is a small municipality in the Brussels-Capital Region of Belgium, known for the National Basilica of the Sacred Heart that dominates its skyline.
-
B.
Schaerbeek
Schaerbeek is a multicultural municipality in the Brussels-Capital Region of Belgium, known for its Art Nouveau architecture and urban character.
-
C.
Borsbeek
Borsbeek is a small municipality in the Belgian province of Antwerp, known for its suburban character and proximity to the city of Antwerp.
-
D.
Linkebeek
Linkebeek is a small Flemish municipality in the Belgian province of Flemish Brabant, located just south of Brussels.
-
E.
Diegem
Diegem is a village in Flemish Brabant, Belgium, known for its proximity to Brussels Airport and its role as a commercial and office hub.
- 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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7ee4f4a08190ada5ee14fec2b822 |
completed | April 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d189e601508190b116fca9854057bc |
completed | April 4, 2026, 10 p.m. |
Created at: March 30, 2026, 7:50 p.m.