Triple
T1426418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Flanders |
E30340
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Knokke-Heist |
E251947
|
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: Knokke-Heist | Statement: [West Flanders, hasMunicipality, Knokke-Heist]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Knokke-Heist Context triple: [West Flanders, hasMunicipality, Knokke-Heist]
-
A.
Knokke-Heist
chosen
Knokke-Heist is a Belgian coastal resort town known for its beaches, upscale tourism, and proximity to the Dutch border.
-
B.
Laeken
Laeken is a residential district in the north of Brussels, Belgium, known for its royal palace, extensive parks, and role as the traditional home of the Belgian monarchy.
-
C.
Machelen
Machelen is a municipality in the Belgian province of Flemish Brabant, located just northeast of Brussels and known for its mix of residential areas and business zones near the capital.
-
D.
Roeselare
Roeselare is a city in western Belgium known as an economic and commercial center in the province of West Flanders.
-
E.
Ixelles
Ixelles is a vibrant, multicultural municipality of the Brussels-Capital Region in Belgium, known for its Art Nouveau architecture, lively student population, and cultural institutions.
- 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_69a498fb823c8190a67ce4c4837e641a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c4be7d208190bcfb46239bd72e56 |
completed | March 1, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aea82191408190892e9a8e12504a8f |
completed | March 9, 2026, 10:59 a.m. |
Created at: March 1, 2026, 8 p.m.