Triple
T21912930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wiefelstede |
E541109
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Ammerland |
—
|
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: Ammerland | Statement: [Wiefelstede, partOf, Ammerland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ammerland Context triple: [Wiefelstede, partOf, Ammerland]
-
A.
Ammerland
Ammerland is a locality within the Bavarian municipality of Münsing in Germany, situated near Lake Starnberg.
-
B.
Emsland
Emsland is a rural region in western Germany known for its agriculture, peatlands, and location along the River Ems near the Dutch border.
-
C.
Ammerland (district)
chosen
Ammerland is a rural district in Lower Saxony, Germany, known for its peatlands, tree nurseries, and the spa town of Bad Zwischenahn.
-
D.
Harkstede
Harkstede is a village in the Dutch province of Groningen, known for its rural character and proximity to the city of Groningen.
-
E.
Pinneberg
Pinneberg is a town in northern Germany that serves as the administrative center of the district of the same name near Hamburg.
- 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_69e0c47c4b9c8190a5586a75f5f36453 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f121db1dc48190af5dc634431d863a |
completed | April 28, 2026, 9:08 p.m. |
Created at: April 16, 2026, 7:41 p.m.