Triple
T6142486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trondheim |
E136993
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
Bakklandet
Bakklandet is a historic, picturesque neighborhood in Trondheim, Norway, known for its colorful wooden houses, cobbled streets, and riverside cafés.
|
E570933
|
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: Bakklandet | Statement: [Trondheim, hasLandmark, Bakklandet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bakklandet Context triple: [Trondheim, hasLandmark, Bakklandet]
-
A.
Kalbakken
Kalbakken is a residential neighborhood in Oslo, Norway, known for its apartment blocks, green areas, and access to public transportation.
-
B.
Haugalandet
Haugalandet is a coastal region in western Norway centered around the town of Haugesund, known for its maritime heritage and North Sea industries.
-
C.
Akkerhaugen
Akkerhaugen is a small village in Telemark, Norway, known for its scenic lakeside setting and role as a local hub for tourism and agriculture.
-
D.
Bjugn
Bjugn is a former municipality and coastal community in Trøndelag county, Norway, known for its fishing, agriculture, and location on the Fosen peninsula.
-
E.
Brekstad
Brekstad is a coastal town in central Norway that serves as an administrative and commercial center for the Fosen region.
- 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: Bakklandet Triple: [Trondheim, hasLandmark, Bakklandet]
Generated description
Bakklandet is a historic, picturesque neighborhood in Trondheim, Norway, known for its colorful wooden houses, cobbled streets, and riverside cafés.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bakklandet Target entity description: Bakklandet is a historic, picturesque neighborhood in Trondheim, Norway, known for its colorful wooden houses, cobbled streets, and riverside cafés.
-
A.
Kalbakken
Kalbakken is a residential neighborhood in Oslo, Norway, known for its apartment blocks, green areas, and access to public transportation.
-
B.
Haugalandet
Haugalandet is a coastal region in western Norway centered around the town of Haugesund, known for its maritime heritage and North Sea industries.
-
C.
Akkerhaugen
Akkerhaugen is a small village in Telemark, Norway, known for its scenic lakeside setting and role as a local hub for tourism and agriculture.
-
D.
Bjugn
Bjugn is a former municipality and coastal community in Trøndelag county, Norway, known for its fishing, agriculture, and location on the Fosen peninsula.
-
E.
Brekstad
Brekstad is a coastal town in central Norway that serves as an administrative and commercial center for the Fosen region.
- 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_69c008a2c6308190a56519b22d55d083 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05cb387ac8190a60579b59a741425 |
completed | March 22, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c135f2defc8190a666f82e230a51c2 |
completed | March 23, 2026, 12:45 p.m. |
| NEDg | Description generation | batch_69c13679dd58819099036d1119fa370b |
completed | March 23, 2026, 12:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c1376db6a0819087c0d0aebc2e2b3e |
completed | March 23, 2026, 12:51 p.m. |
Created at: March 22, 2026, 4:16 p.m.