Triple
T3661500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bodø |
E77659
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Nordland county
Nordland county is a long, coastal region in northern Norway known for its dramatic fjords, islands, and Arctic landscapes.
|
E401032
|
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: Nordland county | Statement: [Bodø, locatedIn, Nordland county]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nordland county Context triple: [Bodø, locatedIn, Nordland county]
-
A.
Møre og Romsdal
Møre og Romsdal is a coastal county in western Norway known for its dramatic fjords, islands, and mountainous landscapes.
-
B.
Oppland
Oppland is a former inland county in southeastern Norway known for its mountainous terrain, national parks, and popular skiing and hiking areas.
-
C.
Troms og Finnmark
Troms og Finnmark is Norway’s northernmost and largest county, known for its Arctic landscapes, Sami culture, and phenomena like the midnight sun and northern lights.
-
D.
Sogn og Fjordane
Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
-
E.
Finnmark
Finnmark is a sparsely populated, historically Norwegian region in the far northeast of Scandinavia, known for its Arctic climate, Sami culture, and dramatic coastal and tundra landscapes.
- 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: Nordland county Triple: [Bodø, locatedIn, Nordland county]
Generated description
Nordland county is a long, coastal region in northern Norway known for its dramatic fjords, islands, and Arctic landscapes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nordland county Target entity description: Nordland county is a long, coastal region in northern Norway known for its dramatic fjords, islands, and Arctic landscapes.
-
A.
Møre og Romsdal
Møre og Romsdal is a coastal county in western Norway known for its dramatic fjords, islands, and mountainous landscapes.
-
B.
Oppland
Oppland is a former inland county in southeastern Norway known for its mountainous terrain, national parks, and popular skiing and hiking areas.
-
C.
Troms og Finnmark
Troms og Finnmark is Norway’s northernmost and largest county, known for its Arctic landscapes, Sami culture, and phenomena like the midnight sun and northern lights.
-
D.
Sogn og Fjordane
Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
-
E.
Finnmark
Finnmark is a sparsely populated, historically Norwegian region in the far northeast of Scandinavia, known for its Arctic climate, Sami culture, and dramatic coastal and tundra landscapes.
- 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3d826d88190b0b50e8592088a36 |
completed | March 8, 2026, 6:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5336401bc81908f305cb91c53f934 |
completed | March 14, 2026, 10:07 a.m. |
| NEDg | Description generation | batch_69b534343a4081909495add7f524cbd2 |
completed | March 14, 2026, 10:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b534931f188190a9428f1b81e524a4 |
completed | March 14, 2026, 10:12 a.m. |
Created at: March 8, 2026, 3:25 p.m.