Triple
T15109921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mariahout |
E360883
|
entity |
| Predicate | nearbyPlace |
P2064
|
FINISHED |
| Object | Beek en Donk |
E379457
|
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: Beek en Donk | Statement: [Mariahout, nearbyPlace, Beek en Donk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beek en Donk Context triple: [Mariahout, nearbyPlace, Beek en Donk]
-
A.
Beek en Donk
chosen
Beek en Donk is a village in the province of North Brabant in the southern Netherlands, known for its rural character and proximity to other small settlements.
-
B.
Woudwetering
Woudwetering is a Dutch waterway in South Holland that serves as an important local canal near the village of Woubrugge.
-
C.
Schipbeek
Schipbeek is a small river in the eastern Netherlands that flows through the provinces of Overijssel and Gelderland before joining the IJssel.
-
D.
Bodegraven
Bodegraven is a town in the Dutch province of South Holland, known for its cheese production and location in the Green Heart region of the Netherlands.
-
E.
Oud-Waterschei
Oud-Waterschei is a neighborhood of the Belgian city of Genk, historically known for its coal mining heritage and associated garden city architecture.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0058c04f481909deeac0271d961b6 |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a61136081908198806944c81808 |
completed | May 9, 2026, 11:28 a.m. |
Created at: April 10, 2026, 3:05 a.m.