Triple
T13021702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harderwijk |
E326186
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Nunspeet |
—
|
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: Nunspeet | Statement: [Harderwijk, borderedBy, Nunspeet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nunspeet Context triple: [Harderwijk, borderedBy, Nunspeet]
-
A.
Nunspeet
chosen
Nunspeet is a Dutch town and municipality on the Veluwe known for its forests, heathlands, and role as a popular nature and holiday destination.
-
B.
Hansweert
Hansweert is a small village in the Dutch province of Zeeland, known historically as a canal and shipping hub along the Western Scheldt.
-
C.
Yerseke
Yerseke is a Dutch village in the province of Zeeland, best known for its mussel and oyster farming along the Eastern Scheldt.
-
D.
Deurne
Deurne is a district of the Belgian city of Antwerp, known for its residential neighborhoods and green spaces such as Rivierenhof park.
-
E.
Deurne
Deurne is a municipality in the Dutch province of North Brabant, known for its rural character and historic peat extraction areas.
- 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97ed05e9c8190a4f208662bca0602 |
completed | April 10, 2026, 10:50 p.m. |
Created at: April 9, 2026, 8:52 p.m.