Triple
T20766613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Veldhoven |
E511113
|
entity |
| Predicate | partOfRegion |
P285
|
FINISHED |
| Object | Kempenland |
—
|
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: Kempenland | Statement: [Veldhoven, partOfRegion, Kempenland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kempenland Context triple: [Veldhoven, partOfRegion, Kempenland]
-
A.
Kempenlands
Kempenlands is a regional variety of the Brabantian dialect spoken in the Kempen area of the Low Countries.
-
B.
Dinkelland
Dinkelland is a rural municipality in the eastern Netherlands, located in the Twente region of the province of Overijssel near the German border.
-
C.
Kempen
chosen
Kempen is a historical region in the Low Countries, spanning parts of present-day Belgium and the Netherlands, known for its sandy soils, heathlands, and rural character.
-
D.
Lansingerland
Lansingerland is a Dutch municipality in the province of South Holland, known for its suburban communities and greenhouse horticulture near the city of Rotterdam.
-
E.
Kamperland
Kamperland is a village in the Dutch province of Zeeland, located on the island of Noord-Beveland and known as a coastal and recreational destination.
- 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_69e0b4ca01148190ac018e57e0cab46f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c24ceab8819094e331c57abe6879 |
completed | April 21, 2026, 12:18 a.m. |
Created at: April 16, 2026, 12:36 p.m.