Triple
T10220443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wagenborgen |
E242560
|
entity |
| Predicate | hasNeighbouringSettlement |
P4647
|
FINISHED |
| Object | Siddeburen |
E242566
|
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: Siddeburen | Statement: [Wagenborgen, hasNeighbouringSettlement, Siddeburen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siddeburen Context triple: [Wagenborgen, hasNeighbouringSettlement, Siddeburen]
-
A.
Siddeburen
chosen
Siddeburen is a village in the Dutch province of Groningen, located within the municipality of Eemsdelta.
-
B.
Badbergen
Badbergen is a municipality in Lower Saxony, Germany, known for its rural character and location within the Osnabrück district.
-
C.
Osendarp
Osendarp is a Dutch surname most notably associated with Tinus Osendarp, a sprinter who competed in the 1936 Berlin Olympics.
-
D.
Beinsdorp
Beinsdorp is a small village in the Dutch province of North Holland, situated within the municipality of Haarlemmermeer.
-
E.
Steenbergen
Steenbergen is a municipality and town in the Dutch province of North Brabant, known for its rural landscape and proximity to several major waterways.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa72b258819097d8d50a714e19dc |
completed | April 6, 2026, 12:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f70a23288190a1dbb67324cfd799 |
completed | April 9, 2026, 12:47 a.m. |
Created at: April 6, 2026, 11:09 a.m.