Triple
T23149714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meijel |
E578288
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Peel en Maas |
E625342
|
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: Peel en Maas | Statement: [Meijel, partOf, Peel en Maas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peel en Maas Context triple: [Meijel, partOf, Peel en Maas]
-
A.
Peel en Maas
chosen
Peel en Maas is a municipality in the Dutch province of Limburg, known for its rural character, historic villages, and location along the river Maas.
-
B.
Afgedamde Maas
The Afgedamde Maas is a canalised branch of the River Maas in the Netherlands, created by damming and rerouting the original river to improve flood control and navigation.
-
C.
Binnenmaas
Binnenmaas was a former municipality in the Dutch province of South Holland, named after the nearby lake and comprising several villages in the Hoeksche Waard region.
-
D.
Maasgouw
Maasgouw is a municipality in the Dutch province of Limburg, known for its historic villages and location along the river Maas.
-
E.
Krimpen aan den IJssel
Krimpen aan den IJssel is a Dutch town and municipality situated along the Hollandse IJssel river, forming part of the Rotterdam metropolitan area.
- 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_69e245fb8de081908f0eba7b5fd75bc4 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18ed0b76c8190ac61b949d88e9970 |
completed | April 29, 2026, 4:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c3098168481908aa4e4a985314db1 |
completed | May 19, 2026, 9:42 a.m. |
Created at: April 17, 2026, 4:01 p.m.