Triple
T7128490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Solvang |
E166125
|
entity |
| Predicate | hasSisterCity |
P919
|
FINISHED |
| Object |
Skagen
Skagen is Denmark’s northernmost town, renowned for its picturesque fishing harbor, distinctive yellow houses, and the scenic meeting point of the North Sea and Baltic Sea.
|
E643713
|
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: Skagen | Statement: [Solvang, hasSisterCity, Skagen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skagen Context triple: [Solvang, hasSisterCity, Skagen]
-
A.
Skagen
Skagen is a minimalist Danish-inspired watch and accessories brand known for its clean design aesthetic and modern, affordable timepieces.
-
B.
Swatch
Swatch is a Swiss watchmaker best known for its colorful, affordable fashion watches that helped revitalize the Swiss watch industry in the 1980s.
-
C.
Daniel Wellington
Daniel Wellington is a Swedish watch brand known for its minimalist, fashion-oriented timepieces with interchangeable NATO and leather straps.
-
D.
Tissot
Tissot is a Swiss watchmaker renowned for its affordable yet high-quality timepieces and long heritage in traditional and sports-oriented horology.
-
E.
Brøgger
Brøgger is a Danish surname most notably associated with writer and cultural critic Suzanne Brøgger.
- 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: Skagen Triple: [Solvang, hasSisterCity, Skagen]
Generated description
Skagen is Denmark’s northernmost town, renowned for its picturesque fishing harbor, distinctive yellow houses, and the scenic meeting point of the North Sea and Baltic Sea.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Skagen Target entity description: Skagen is Denmark’s northernmost town, renowned for its picturesque fishing harbor, distinctive yellow houses, and the scenic meeting point of the North Sea and Baltic Sea.
-
A.
Skagen
Skagen is a minimalist Danish-inspired watch and accessories brand known for its clean design aesthetic and modern, affordable timepieces.
-
B.
Swatch
Swatch is a Swiss watchmaker best known for its colorful, affordable fashion watches that helped revitalize the Swiss watch industry in the 1980s.
-
C.
Daniel Wellington
Daniel Wellington is a Swedish watch brand known for its minimalist, fashion-oriented timepieces with interchangeable NATO and leather straps.
-
D.
Tissot
Tissot is a Swiss watchmaker renowned for its affordable yet high-quality timepieces and long heritage in traditional and sports-oriented horology.
-
E.
Brøgger
Brøgger is a Danish surname most notably associated with writer and cultural critic Suzanne Brøgger.
- 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_69c6888350588190870cd552b427a1cd |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e66b230c819090ddbc5396868305 |
completed | March 27, 2026, 8:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7a338b6908190bace3ee43a080c2f |
completed | March 28, 2026, 9:45 a.m. |
| NEDg | Description generation | batch_69c7a446c5088190908dd7b4cdc57f18 |
completed | March 28, 2026, 9:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7a4fc9f788190b38437c6e91a5f8a |
completed | March 28, 2026, 9:53 a.m. |
Created at: March 27, 2026, 2:44 p.m.