Triple
T5658836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flemish Limburg |
E124685
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
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.
|
E628807
|
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: Diepenbeek | Statement: [Flemish Limburg, hasMunicipality, Diepenbeek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diepenbeek Context triple: [Flemish Limburg, hasMunicipality, Diepenbeek]
-
A.
Lembeek
Lembeek is a village in the Belgian municipality of Halle, located along the Senne River in the province of Flemish Brabant.
-
B.
Bellebeek
Bellebeek is a small stream in Belgium that serves as a right-bank tributary of the River Dender.
-
C.
Meerbeke
Meerbeke is a village in East Flanders, Belgium, best known for having long served as the traditional finish town of the Tour of Flanders cycling race.
-
D.
Borgerhout
Borgerhout is a densely populated, multicultural district of the Belgian city of Antwerp, known for its vibrant street life and diverse communities.
-
E.
Merelbeke
Merelbeke is a municipality in East Flanders, Belgium, known in part for hosting Ghent University's Faculty of Veterinary Medicine.
- 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: Diepenbeek Triple: [Flemish Limburg, hasMunicipality, Diepenbeek]
Generated description
Diepenbeek is a municipality in the Belgian province of Limburg, known for its blend of residential areas, industry, and the campus of Hasselt University.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Diepenbeek Target entity description: Diepenbeek is a municipality in the Belgian province of Limburg, known for its blend of residential areas, industry, and the campus of Hasselt University.
-
A.
Lembeek
Lembeek is a village in the Belgian municipality of Halle, located along the Senne River in the province of Flemish Brabant.
-
B.
Bellebeek
Bellebeek is a small stream in Belgium that serves as a right-bank tributary of the River Dender.
-
C.
Meerbeke
Meerbeke is a village in East Flanders, Belgium, best known for having long served as the traditional finish town of the Tour of Flanders cycling race.
-
D.
Borgerhout
Borgerhout is a densely populated, multicultural district of the Belgian city of Antwerp, known for its vibrant street life and diverse communities.
-
E.
Merelbeke
Merelbeke is a municipality in East Flanders, Belgium, known in part for hosting Ghent University's Faculty of Veterinary Medicine.
- 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_69c0082774a481909d7e63fb2aad56ac |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022fd9b148190bd4aa9c43500949f |
completed | March 22, 2026, 5:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c750f84be081908fa4738e09cb884e |
completed | March 28, 2026, 3:54 a.m. |
| NEDg | Description generation | batch_69c7524d677c81909531ba9bb46f2632 |
completed | March 28, 2026, 4 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c752bef2808190843f3cad53aa5702 |
completed | March 28, 2026, 4:02 a.m. |
Created at: March 22, 2026, 3:42 p.m.