Triple
T19503584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Land van Cuijk |
E487964
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Langenboom |
—
|
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: Langenboom | Statement: [Land van Cuijk, containsSettlement, Langenboom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Langenboom Context triple: [Land van Cuijk, containsSettlement, Langenboom]
-
A.
Langenboom
chosen
Langenboom is a village in the Dutch province of North Brabant, known as a small rural community within the municipality of Mill en Sint Hubert.
-
B.
Bommershoven
Bommershoven is a village in the Belgian province of Limburg that forms one of the municipal sections of the city of Borgloon.
-
C.
Uithoorn
Uithoorn is a town and municipality in the province of North Holland in the Netherlands, situated along the Amstel River.
-
D.
Groesbeek
Groesbeek is a village in the Dutch province of Gelderland, known for its hilly landscape, World War II history, and wine production.
-
E.
Vinkeveen
Vinkeveen is a Dutch village in the province of Utrecht, best known for its lakes and recreational water activities.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6350f8d888190a4809c83522933d4 |
completed | April 20, 2026, 2:15 p.m. |
Created at: April 10, 2026, 1:40 p.m.