Triple
T16987433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maas-Waal Canal |
E412104
|
entity |
| Predicate | crossesMunicipality |
P13729
|
FINISHED |
| Object | Wijchen |
—
|
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: Wijchen | Statement: [Maas-Waal Canal, crossesMunicipality, Wijchen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wijchen Context triple: [Maas-Waal Canal, crossesMunicipality, Wijchen]
-
A.
Wijchen
chosen
Wijchen is a town and municipality in the Dutch province of Gelderland, located just southwest of the city of Nijmegen.
-
B.
Sittard
Sittard is a historic city in the Dutch province of Limburg, known for its medieval center and proximity to the German and Belgian borders.
-
C.
Gorinchem
Gorinchem is a historic fortified city in the Netherlands known for its well-preserved city walls and picturesque old town.
-
D.
Roermond
Roermond is a historic city in the southeastern Netherlands known for its medieval architecture, prominent churches, and large designer outlet shopping center.
-
E.
Harderwijk
Harderwijk is a historic Dutch city known for its former Hanseatic trading role and scenic location on the shores of the Veluwemeer.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d27cd2048190800a60ae653e11e1 |
completed | April 18, 2026, 6:50 p.m. |
Created at: April 10, 2026, 5:32 a.m.