Triple
T11360067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buchholz in der Nordheide |
E269061
|
entity |
| Predicate | hasNeighbouringCity |
P3883
|
FINISHED |
| Object | Tostedt |
E794380
|
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: Tostedt | Statement: [Buchholz in der Nordheide, hasNeighbouringCity, Tostedt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tostedt Context triple: [Buchholz in der Nordheide, hasNeighbouringCity, Tostedt]
-
A.
Tostedt
chosen
Tostedt is a small municipality in Lower Saxony, Germany, located southwest of Hamburg.
-
B.
Tönisvorst
Tönisvorst is a small town in North Rhine-Westphalia, western Germany, known for its agricultural surroundings and proximity to the city of Krefeld.
-
C.
Tost
Tost is a town in present-day Toszek, Poland, historically part of Upper Silesia.
-
D.
Tosterön
Tosterön is an island in Lake Mälaren in central Sweden, known for its natural landscapes and proximity to the town of Strängnäs.
-
E.
Oberkrämer
Oberkrämer is a rural municipality in the Oberhavel district of Brandenburg, Germany, known for its villages, agricultural landscape, and proximity to Berlin.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea42fe608190b9c71dd63f8780f3 |
completed | April 9, 2026, 6:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e543bdd6d88190b4f816ffde5179be |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 8, 2026, 9:33 p.m.