Triple
T10473074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koksijde |
E246975
|
entity |
| Predicate | hasMunicipalSection |
P10450
|
FINISHED |
| Object | Koksijde (town) |
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 (town) | Statement: [Koksijde, hasMunicipalSection, Koksijde (town)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koksijde (town) Context triple: [Koksijde, hasMunicipalSection, Koksijde (town)]
-
A.
Koksijde
chosen
Koksijde is a coastal municipality in West Flanders, Belgium, known for its North Sea beaches and seaside tourism.
-
B.
Kenderes
Kenderes is a town in Hungary best known as the birthplace and family estate center of Regent Miklós Horthy.
-
C.
Boskoop
Boskoop is a Dutch town historically renowned as a major center of tree and nursery cultivation.
-
D.
Ankum
Ankum is a municipality in Lower Saxony, Germany, situated within the Osnabrück district.
-
E.
Koshice
Košice is the second-largest city in Slovakia, known for its well-preserved medieval old town and status as an important cultural and economic center in the country.
- 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.