Triple
T17645306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rivierenland |
E429339
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Druten |
—
|
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: Druten | Statement: [Rivierenland, contains, Druten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Druten Context triple: [Rivierenland, contains, Druten]
-
A.
Druten
chosen
Druten is a municipality and town in the Dutch province of Gelderland, located along the river Waal in the eastern Netherlands.
-
B.
Leusden
Leusden is a Dutch town and municipality in the central Netherlands, known for its green residential character and proximity to the city of Amersfoort.
-
C.
Loosdrecht
Loosdrecht is a Dutch village in the province of North Holland, best known for its scenic lakes and water sports tourism.
-
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_69d889e2c2608190b762e76d9b2262f1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46e382ba88190af19d0e3b8c8cadd |
completed | April 19, 2026, 5:55 a.m. |
Created at: April 10, 2026, 6:04 a.m.