Triple
T17052975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dinkelland |
E413747
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Denekamp |
E1251073
|
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: Denekamp | Statement: [Dinkelland, containsSettlement, Denekamp]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Denekamp Context triple: [Dinkelland, containsSettlement, Denekamp]
-
A.
Denekamp
chosen
Denekamp is a town in the eastern Netherlands that serves as the administrative center of the municipality of Dinkelland in the province of Overijssel.
-
B.
Koekamp
Koekamp is a historic green park and deer reserve on the edge of central The Hague in the Netherlands.
-
C.
Harskamp
Harskamp is a village in the Dutch province of Gelderland, known for its rural character and proximity to the Hoge Veluwe National Park.
-
D.
Camperduin
Camperduin is a coastal village in North Holland, Netherlands, historically notable as the namesake of the naval Battle of Camperdown.
-
E.
Reeshof
Reeshof is a large residential district in the western part of Tilburg in the Netherlands, known for its modern housing developments and green spaces.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3daa491008190ad013ee37532aa51 |
completed | April 18, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01413eba788190982351a97286e81f |
completed | May 11, 2026, 2:38 a.m. |
Created at: April 10, 2026, 5:34 a.m.