Triple
T19507789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meråker |
E488069
|
entity |
| Predicate | hasLake |
P1025
|
FINISHED |
| Object |
Torsbjørka
Torsbjørka is a lake located in the municipality of Meråker in Trøndelag county, central Norway.
|
E1393691
|
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: Torsbjørka | Statement: [Meråker, hasLake, Torsbjørka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Torsbjørka Context triple: [Meråker, hasLake, Torsbjørka]
-
A.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
B.
Digerberget
Digerberget is a hill or small mountain located within Nora Municipality in central Sweden, known for its surrounding forests and outdoor recreation opportunities.
-
C.
Kjerkeberget
Kjerkeberget is a forested hill in Norway that marks the highest natural point within Oslo’s municipal boundaries.
-
D.
Vartdal
Vartdal is a small village in Ørsta Municipality in Møre og Romsdal county, Norway, situated along the Vartdalsfjorden on the western coast.
-
E.
Brattvåg
Brattvåg is a small coastal village in western Norway known for its maritime industry and scenic fjord landscape.
- 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: Torsbjørka Triple: [Meråker, hasLake, Torsbjørka]
Generated description
Torsbjørka is a lake located in the municipality of Meråker in Trøndelag county, central Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Torsbjørka Target entity description: Torsbjørka is a lake located in the municipality of Meråker in Trøndelag county, central Norway.
-
A.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
B.
Digerberget
Digerberget is a hill or small mountain located within Nora Municipality in central Sweden, known for its surrounding forests and outdoor recreation opportunities.
-
C.
Kjerkeberget
Kjerkeberget is a forested hill in Norway that marks the highest natural point within Oslo’s municipal boundaries.
-
D.
Vartdal
Vartdal is a small village in Ørsta Municipality in Møre og Romsdal county, Norway, situated along the Vartdalsfjorden on the western coast.
-
E.
Brattvåg
Brattvåg is a small coastal village in western Norway known for its maritime industry and scenic fjord landscape.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e635130e708190bb3d70e1abbade2a |
completed | April 20, 2026, 2:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07bd4c2de48190843b04b1a1eeaa8f |
completed | May 16, 2026, 12:41 a.m. |
| NEDg | Description generation | batch_6a07bde28e848190aaa9c4a06b31bdb6 |
completed | May 16, 2026, 12:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07bed9c62c819088d8e32f92b3b147 |
completed | May 16, 2026, 12:48 a.m. |
Created at: April 10, 2026, 1:40 p.m.