Triple
T831349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trøndelag |
E17971
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Namsos
Namsos is a coastal town and municipality in central Norway known for its timber industry, fjord-side location, and role as a regional service center in Trøndelag.
|
E100031
|
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: Namsos | Statement: [Trøndelag, contains, Namsos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Namsos Context triple: [Trøndelag, contains, Namsos]
-
A.
Ringerike
Ringerike is a historic district and municipality in southeastern Norway known for its rich Viking-age heritage and distinctive cultural traditions.
-
B.
Senja
Senja is Norway’s second-largest island, renowned for its dramatic coastal mountains, fishing villages, and scenic Arctic landscapes.
-
C.
Narvik
Narvik is a port town in northern Norway known for its strategic importance during World War II and as the site of major naval and land battles.
-
D.
Sotra
Sotra is a large, populated island off the west coast of Norway, known for its rugged coastline, fishing communities, and proximity to the city of Bergen.
-
E.
Niseko
Niseko is a renowned ski resort area in northern Japan famous for its abundant light powder snow, extensive slopes, and vibrant international winter sports scene.
- 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: Namsos Triple: [Trøndelag, contains, Namsos]
Generated description
Namsos is a coastal town and municipality in central Norway known for its timber industry, fjord-side location, and role as a regional service center in Trøndelag.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Namsos Target entity description: Namsos is a coastal town and municipality in central Norway known for its timber industry, fjord-side location, and role as a regional service center in Trøndelag.
-
A.
Ringerike
Ringerike is a historic district and municipality in southeastern Norway known for its rich Viking-age heritage and distinctive cultural traditions.
-
B.
Senja
Senja is Norway’s second-largest island, renowned for its dramatic coastal mountains, fishing villages, and scenic Arctic landscapes.
-
C.
Narvik
Narvik is a port town in northern Norway known for its strategic importance during World War II and as the site of major naval and land battles.
-
D.
Sotra
Sotra is a large, populated island off the west coast of Norway, known for its rugged coastline, fishing communities, and proximity to the city of Bergen.
-
E.
Niseko
Niseko is a renowned ski resort area in northern Japan famous for its abundant light powder snow, extensive slopes, and vibrant international winter sports scene.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abb4be948190ae757df85bdc40e4 |
completed | March 1, 2026, 9:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7929458648190a88390a1a3207ad0 |
completed | March 4, 2026, 2:01 a.m. |
| NEDg | Description generation | batch_69a796c83a888190a595c76c9d94105b |
completed | March 4, 2026, 2:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7971e8eb88190a1aae5e03f8ea928 |
completed | March 4, 2026, 2:21 a.m. |
Created at: March 1, 2026, 7:38 p.m.