Triple
T7013180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norderney |
E162633
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Norderney (town) |
E162633
|
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: Norderney (town) | Statement: [Norderney, hasSettlement, Norderney (town)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norderney (town) Context triple: [Norderney, hasSettlement, Norderney (town)]
-
A.
Norderney
chosen
Norderney is a popular German North Sea island known for its sandy beaches, seaside resort town, and role as a major tourist destination in Lower Saxony.
-
B.
Groß Borstel
Groß Borstel is a residential district of Hamburg, Germany, situated near Hamburg Airport and characterized by a mix of urban housing and green spaces.
-
C.
Husum
Husum is a small coastal town in northern Germany known for its North Sea harbor, maritime heritage, and role as a local cultural and commercial center.
-
D.
Aurich
Aurich is a historic town in northwestern Germany that serves as one of the principal urban centers of the East Frisia region in Lower Saxony.
-
E.
Elmshorn
Elmshorn is a town in northern Germany’s Schleswig-Holstein state, known as an industrial and commuter hub northwest of Hamburg.
- 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_69c6885a127c8190867b059bdccf13ff |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc58b04c8190af4913dbaf43c3d4 |
completed | March 27, 2026, 7:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c76a4ff6148190a7a453328507fd6b |
completed | March 28, 2026, 5:42 a.m. |
Created at: March 27, 2026, 2:34 p.m.