Triple
T6754644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Limburg (Belgium) |
E154423
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Bilzen |
E627953
|
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: Bilzen | Statement: [Limburg (Belgium), contains, Bilzen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bilzen Context triple: [Limburg (Belgium), contains, Bilzen]
-
A.
Bilzen
chosen
Bilzen is a historic city and municipality in the Belgian province of Limburg, known for its medieval heritage and the nearby Alden Biesen Castle.
-
B.
Lembeek
Lembeek is a village in the Belgian municipality of Halle, located along the Senne River in the province of Flemish Brabant.
-
C.
Willebroek
Willebroek is a municipality in northern Belgium known for its canal connections and location between Brussels and Antwerp.
-
D.
Zonhoven
Zonhoven is a municipality in the Belgian province of Limburg, known for its green surroundings and proximity to the city of Hasselt.
-
E.
Borgerhout
Borgerhout is a densely populated, multicultural district of the Belgian city of Antwerp, known for its vibrant street life and diverse communities.
- 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_69c6880fd5808190be684854081e27dd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1f465388190858207ca4c48f18d |
completed | March 27, 2026, 6:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c96bf63cfc8190a89a674e0e666134 |
completed | March 29, 2026, 6:14 p.m. |
Created at: March 27, 2026, 2:11 p.m.