Triple
T2404242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Het Hogeland |
E50238
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Kloosterburen
Kloosterburen is a small village in the Dutch province of Groningen, known for its historic churches and rural character.
|
E526980
|
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: Kloosterburen | Statement: [Het Hogeland, containsSettlement, Kloosterburen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kloosterburen Context triple: [Het Hogeland, containsSettlement, Kloosterburen]
-
A.
Veldhoven
Veldhoven is a town and municipality in the southern Netherlands, located near Eindhoven in the province of North Brabant.
-
B.
Oosterhout
Oosterhout is a town and municipality in the southern Netherlands known for its historic monasteries and proximity to the city of Breda.
-
C.
Scharendijke
Scharendijke is a village in the Dutch province of Zeeland, known as a popular base for water sports and diving in the Grevelingen and North Sea area.
-
D.
Bloemendaal
Bloemendaal is a coastal municipality in North Holland, Netherlands, known for its beaches, dunes, and affluent residential areas.
-
E.
Deurne
Deurne is a district of the Belgian city of Antwerp, known for its residential neighborhoods and green spaces such as Rivierenhof park.
- 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: Kloosterburen Triple: [Het Hogeland, containsSettlement, Kloosterburen]
Generated description
Kloosterburen is a small village in the Dutch province of Groningen, known for its historic churches and rural character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kloosterburen Target entity description: Kloosterburen is a small village in the Dutch province of Groningen, known for its historic churches and rural character.
-
A.
Veldhoven
Veldhoven is a town and municipality in the southern Netherlands, located near Eindhoven in the province of North Brabant.
-
B.
Oosterhout
Oosterhout is a town and municipality in the southern Netherlands known for its historic monasteries and proximity to the city of Breda.
-
C.
Scharendijke
Scharendijke is a village in the Dutch province of Zeeland, known as a popular base for water sports and diving in the Grevelingen and North Sea area.
-
D.
Bloemendaal
Bloemendaal is a coastal municipality in North Holland, Netherlands, known for its beaches, dunes, and affluent residential areas.
-
E.
Deurne
Deurne is a district of the Belgian city of Antwerp, known for its residential neighborhoods and green spaces such as Rivierenhof park.
- 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc8fa151081909bc6be528b29b315 |
completed | March 7, 2026, 6:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfd2366a3c819097391ad8731c21a8 |
completed | March 22, 2026, 11:27 a.m. |
| NEDg | Description generation | batch_69bfd2b9290c819092ca7d3b29d8f39b |
completed | March 22, 2026, 11:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bfd3180ac081908711bd893d811c84 |
completed | March 22, 2026, 11:31 a.m. |
Created at: March 4, 2026, 7:58 p.m.