Triple
T21333932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Netherlands |
E525986
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Bunschoten |
—
|
NE NERFINISHED |
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: Bunschoten | Statement: [Central Netherlands, containsCity, Bunschoten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bunschoten Context triple: [Central Netherlands, containsCity, Bunschoten]
-
A.
Bunschoten
chosen
Bunschoten is a Dutch town and municipality known for its traditional fishing heritage and historic village character in the central Netherlands.
-
B.
Bommershoven
Bommershoven is a village in the Belgian province of Limburg that forms one of the municipal sections of the city of Borgloon.
-
C.
Bilthoven
Bilthoven is a town in the Dutch province of Utrecht, known as a residential suburb with good rail connections and several national research institutes.
-
D.
Zandhoven
Zandhoven is a municipality in the Belgian province of Antwerp, known for its rural character and village communities.
-
E.
Groesbeek
Groesbeek is a village in the Dutch province of Gelderland, known for its hilly landscape, World War II history, and wine production.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b51b90788190a4dd823d962626da |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee5ba65c4081908b93d5dc6a937cb6 |
completed | April 26, 2026, 6:38 p.m. |
Created at: April 16, 2026, 4:43 p.m.