Triple
T7251505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District of Vechta |
E157611
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Vechta |
E217603
|
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: Vechta | Statement: [District of Vechta, hasMunicipality, Vechta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vechta Context triple: [District of Vechta, hasMunicipality, Vechta]
-
A.
Vechta
chosen
Vechta is a town in Lower Saxony, Germany, known for its historical significance, university, and annual Stoppelmarkt fair.
-
B.
Sappemeer
Sappemeer is a town in the province of Groningen in the northeastern Netherlands, historically known for its peat colonies and waterways.
-
C.
Salland
Salland is a historical and rural region in the Dutch province of Overijssel, known for its scenic landscapes, small towns, and agricultural character.
-
D.
Kloosterveen
Kloosterveen is a residential district of the city of Assen in the province of Drenthe in the Netherlands.
-
E.
Monnickendam
Monnickendam is a historic fishing town in North Holland, Netherlands, known for its well-preserved old harbor and traditional Dutch 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_69c6882d81d4819085f7ff862951ee4f |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea7ae0e48190bd80c91bad1976c6 |
completed | March 27, 2026, 8:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c998a68c24819099abe74525830812 |
completed | March 29, 2026, 9:24 p.m. |
Created at: March 27, 2026, 2:56 p.m.