Triple
T11288676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | De Marne |
E267264
|
entity |
| Predicate | hadSettlement |
P16159
|
FINISHED |
| Object | Kloosterburen |
E526980
|
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: Kloosterburen | Statement: [De Marne, hadSettlement, Kloosterburen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kloosterburen Context triple: [De Marne, hadSettlement, Kloosterburen]
-
A.
Kloosterburen
chosen
Kloosterburen is a small village in the Dutch province of Groningen, known for its historic churches and rural character.
-
B.
Schoonhoven
Schoonhoven is a historic Dutch town in South Holland, renowned for its silver craftsmanship and picturesque riverside setting.
-
C.
Veldhoven
Veldhoven is a town and municipality in the southern Netherlands, located near Eindhoven in the province of North Brabant.
-
D.
Oosterhout
Oosterhout is a town and municipality in the southern Netherlands known for its historic monasteries and proximity to the city of Breda.
-
E.
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.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e98875a08190b8509fe55e49d52d |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006065741c8190ad4ceb6bd3d60f9f |
completed | May 10, 2026, 10:39 a.m. |
Created at: April 8, 2026, 9:32 p.m.