Triple
T7620545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merksem |
E172479
|
entity |
| Predicate | hasBorderWith |
P224
|
FINISHED |
| Object | Ekeren |
E263314
|
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: Ekeren | Statement: [Merksem, hasBorderWith, Ekeren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ekeren Context triple: [Merksem, hasBorderWith, Ekeren]
-
A.
Ekeren
chosen
Ekeren is a northern district of the Belgian city of Antwerp, known for its residential character and green spaces.
-
B.
Kesteren
Kesteren is a village in the Dutch province of Gelderland, situated along the Nederrijn river in the central Netherlands.
-
C.
Yerseke
Yerseke is a Dutch village in the province of Zeeland, best known for its mussel and oyster farming along the Eastern Scheldt.
-
D.
Randenbroek
Randenbroek is a historic estate near Amersfoort in the Netherlands, known as the place where the Dutch Golden Age architect and painter Jacob van Campen spent his final years.
-
E.
Grijpskerke
Grijpskerke is a village in the Dutch province of Zeeland, located on the former island of Walcheren.
- 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_69c699506b308190826894dab1d9ea86 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fa62870c8190b17f44eb7a3ff2ad |
completed | March 27, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9953aff988190a3224050e5706589 |
completed | March 29, 2026, 9:10 p.m. |
Created at: March 27, 2026, 3:55 p.m.