Triple
T10473093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koksijde |
E246975
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Veurne |
E164295
|
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: Veurne | Statement: [Koksijde, locatedNear, Veurne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Veurne Context triple: [Koksijde, locatedNear, Veurne]
-
A.
Veurne
chosen
Veurne is a historic town in western Belgium known for its well-preserved medieval center and Flemish Renaissance architecture.
-
B.
Zeewolde
Zeewolde is a Dutch municipality and village known for its modern planned layout and location on reclaimed land in the province of Flevoland.
-
C.
Gavere
Gavere is a municipality in the Belgian province of East Flanders, known for its rural character and several constituent villages.
-
D.
Merelbeke
Merelbeke is a municipality in East Flanders, Belgium, known in part for hosting Ghent University's Faculty of Veterinary Medicine.
-
E.
Woubrugge
Woubrugge is a village in the Dutch province of South Holland, known for its location along waterways and its traditional rural character.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5094daac081908e0ba5e10c1bbb67 |
completed | April 7, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8a0140f4c81908ce95b28e09cb04b |
completed | April 10, 2026, 7 a.m. |
Created at: April 6, 2026, 12:20 p.m.