Triple
T21259108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warendorf district |
E523949
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object | Wadersloh |
—
|
NE NERFINISHED |
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: Wadersloh | Statement: [Warendorf district, containsMunicipality, Wadersloh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wadersloh Context triple: [Warendorf district, containsMunicipality, Wadersloh]
-
A.
Wadersloh
chosen
Wadersloh is a small municipality in North Rhine-Westphalia, Germany, known for its rural character and location in the Münsterland region.
-
B.
Schildwolde
Schildwolde is a village in the Dutch province of Groningen, known for its historic church and rural character within the municipality of Midden-Groningen.
-
C.
Rhauderfehn
Rhauderfehn is a municipality in the East Frisian region of Lower Saxony in northwestern Germany, known for its origins as a peat colony and its characteristic canal landscape.
-
D.
Wiedensahl
Wiedensahl is a small village in Lower Saxony, Germany, best known as the birthplace of the humorist and illustrator Wilhelm Busch.
-
E.
Wilsdruff
Wilsdruff is a small town in the Free State of Saxony in eastern Germany, located near Dresden.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b5156d7881909bd4f83676590715 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735e53df88190bd6024793a0ada08 |
completed | April 21, 2026, 8:31 a.m. |
Created at: April 16, 2026, 3:59 p.m.