Triple
T1009483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gassel |
E21788
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Cuijk |
E444188
|
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: Cuijk | Statement: [Gassel, locatedNear, Cuijk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cuijk Context triple: [Gassel, locatedNear, Cuijk]
-
A.
Cuijk
chosen
Cuijk is a historic town in the Dutch province of North Brabant, known for its Roman-era heritage and location along the River Meuse.
-
B.
Zoeterwoude
Zoeterwoude is a small Dutch municipality and village known for its rural character and location near Leiden in the province of South Holland.
-
C.
Gorinchem
Gorinchem is a historic fortified city in the Netherlands known for its well-preserved city walls and picturesque old town.
-
D.
Harderwijk
Harderwijk is a historic Dutch city known for its former Hanseatic trading role and scenic location on the shores of the Veluwemeer.
-
E.
Apeldoorn
Apeldoorn is a city in the province of Gelderland in the Netherlands, known for the royal palace Het Loo and its historical ties to the Dutch monarchy.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7a3cb608190a2de34a09cd55146 |
completed | March 1, 2026, 10:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bd6f6fe04c8190bffabb9225ef6c2a |
completed | March 20, 2026, 4:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.