Triple
T22748751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamme |
E562631
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Buggenhout |
—
|
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: Buggenhout | Statement: [Hamme, borderedBy, Buggenhout]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buggenhout Context triple: [Hamme, borderedBy, Buggenhout]
-
A.
Buggenhout
chosen
Buggenhout is a municipality in the Belgian province of East Flanders, known for its extensive forest and traditional breweries.
-
B.
Lembeek
Lembeek is a village in the Belgian municipality of Halle, located along the Senne River in the province of Flemish Brabant.
-
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.
Wachtebeke
Wachtebeke is a municipality in the East Flanders province of Belgium, known for its rural character and natural areas such as the Puyenbroeck provincial domain.
-
E.
Zonhoven
Zonhoven is a municipality in the Belgian province of Limburg, known for its green surroundings and proximity to the city of Hasselt.
- 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_69e24551ec7881909a9c924dbea155f6 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179b822988190b5368ac1f4e1d70a |
completed | April 29, 2026, 3:23 a.m. |
Created at: April 17, 2026, 3:24 p.m.