Triple
T10473129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koksijde Air Base |
E246977
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Koksijde |
E246975
|
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: Koksijde | Statement: [Koksijde Air Base, locatedIn, Koksijde]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koksijde Context triple: [Koksijde Air Base, locatedIn, Koksijde]
-
A.
Koksijde
chosen
Koksijde is a coastal municipality in West Flanders, Belgium, known for its North Sea beaches and seaside tourism.
-
B.
Wassenaar
Wassenaar is an affluent coastal town in the western Netherlands known for its wooded estates, beaches, and role as a residential area for diplomats and expatriates.
-
C.
Ankum
Ankum is a municipality in Lower Saxony, Germany, situated within the Osnabrück district.
-
D.
Lonsee
Lonsee is a small municipality in the Alb-Donau district of Baden-Württemberg, Germany, situated on the Swabian Jura near the city of Ulm.
-
E.
Borken
Borken is a town in western Germany that serves as an administrative and commercial center in the state of North Rhine-Westphalia.
- 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_69d8dc68b49481909715c36a4c0e7c4f |
completed | April 10, 2026, 11:18 a.m. |
Created at: April 6, 2026, 12:20 p.m.