Triple
T17264064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denderstreek |
E419077
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Buggenhout
Buggenhout is a municipality in the Belgian province of East Flanders, known for its extensive forest and traditional breweries.
|
E1273602
|
NE FINISHED |
How this triple was built (4 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: [Denderstreek, hasPart, Buggenhout]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buggenhout Context triple: [Denderstreek, hasPart, Buggenhout]
-
A.
Lembeek
Lembeek is a village in the Belgian municipality of Halle, located along the Senne River in the province of Flemish Brabant.
-
B.
Borsbeek
Borsbeek is a small municipality in the Belgian province of Antwerp, known for its suburban character and proximity to the city of Antwerp.
-
C.
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.
-
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.
Diepenbeek
Diepenbeek is a municipality in the Belgian province of Limburg, known for its blend of residential areas, industry, and the campus of Hasselt University.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Buggenhout Triple: [Denderstreek, hasPart, Buggenhout]
Generated description
Buggenhout is a municipality in the Belgian province of East Flanders, known for its extensive forest and traditional breweries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Buggenhout Target entity description: Buggenhout is a municipality in the Belgian province of East Flanders, known for its extensive forest and traditional breweries.
-
A.
Lembeek
Lembeek is a village in the Belgian municipality of Halle, located along the Senne River in the province of Flemish Brabant.
-
B.
Borsbeek
Borsbeek is a small municipality in the Belgian province of Antwerp, known for its suburban character and proximity to the city of Antwerp.
-
C.
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.
-
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.
Diepenbeek
Diepenbeek is a municipality in the Belgian province of Limburg, known for its blend of residential areas, industry, and the campus of Hasselt University.
- F. None of above. chosen
Provenance (5 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42f4432fc81908fd90865822af1fa |
completed | April 19, 2026, 1:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01c929cad08190b0c23cccb011c7f7 |
completed | May 11, 2026, 12:18 p.m. |
| NEDg | Description generation | batch_6a01ca84f3388190aa2eda694f91a17b |
completed | May 11, 2026, 12:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01cb0b3cec8190afc6cf6dd1e4d896 |
completed | May 11, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:40 a.m.