Triple
T7013209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norderney |
E162633
|
entity |
| Predicate | hasAttraction |
P105
|
FINISHED |
| Object |
Nordstrand
Nordstrand is a popular sandy beach area on the North Sea island of Norderney in Germany, known for its coastal scenery and recreational opportunities.
|
E636309
|
NE FINISHED |
How this triple was built (4 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: Nordstrand | Statement: [Norderney, hasAttraction, Nordstrand]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nordstrand Context triple: [Norderney, hasAttraction, Nordstrand]
-
A.
Nordstrand
Nordstrand is a mainly residential borough in the southeastern part of Oslo, Norway, known for its hillside location overlooking the Oslofjord.
-
B.
Sogndalstrand
Sogndalstrand is a historic coastal village in southwestern Norway known for its well-preserved wooden buildings and picturesque harbor setting.
-
C.
Stranda
Stranda is a village and municipality in western Norway known for its scenic fjord landscapes and winter sports opportunities.
-
D.
Farsund
Farsund is a coastal town and municipality in southern Norway known for its maritime heritage, beaches, and historic wooden architecture.
-
E.
Åsgårdstrand
Åsgårdstrand is a small coastal town in Norway best known as a summer retreat and artistic hub associated with painter Edvard Munch.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nordstrand Triple: [Norderney, hasAttraction, Nordstrand]
Generated description
Nordstrand is a popular sandy beach area on the North Sea island of Norderney in Germany, known for its coastal scenery and recreational opportunities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nordstrand Target entity description: Nordstrand is a popular sandy beach area on the North Sea island of Norderney in Germany, known for its coastal scenery and recreational opportunities.
-
A.
Nordstrand
Nordstrand is a mainly residential borough in the southeastern part of Oslo, Norway, known for its hillside location overlooking the Oslofjord.
-
B.
Sogndalstrand
Sogndalstrand is a historic coastal village in southwestern Norway known for its well-preserved wooden buildings and picturesque harbor setting.
-
C.
Stranda
Stranda is a village and municipality in western Norway known for its scenic fjord landscapes and winter sports opportunities.
-
D.
Farsund
Farsund is a coastal town and municipality in southern Norway known for its maritime heritage, beaches, and historic wooden architecture.
-
E.
Åsgårdstrand
Åsgårdstrand is a small coastal town in Norway best known as a summer retreat and artistic hub associated with painter Edvard Munch.
- F. None of above. chosen
Provenance (5 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_69c775656fe48190a9690f5aaca3ba4c |
completed | March 28, 2026, 6:29 a.m. |
| NEDg | Description generation | batch_69c7774e453881909df31386a911cfa4 |
completed | March 28, 2026, 6:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c777d9c29c81908a816aed059ecc96 |
completed | March 28, 2026, 6:40 a.m. |
Created at: March 27, 2026, 2:34 p.m.