Triple

T831368
Position Surface form Disambiguated ID Type / Status
Subject Trøndelag E17971 entity
Predicate hasSubregion P285 FINISHED
Object Fosen
Fosen is a peninsula and traditional district in central Norway known for its coastal landscape, wind farms, and location across the Trondheimsfjord from the city of Trondheim.
 E114916 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: Fosen | Statement: [Trøndelag, hasSubregion, Fosen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fosen
Context triple: [Trøndelag, hasSubregion, Fosen]
  • A. Vestland
    Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
  • B. Lofoten
    Lofoten is a dramatic Arctic archipelago in Norway known for its steep mountains, sheltered bays, fishing villages, and views of the midnight sun and Northern Lights.
  • C. 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.
  • D. Troms
    Troms was a former county in northern Norway known for its Arctic landscapes, coastal fjords, and the city of Tromsø.
  • E. Vesterålen
    Vesterålen is a scenic archipelago in northern Norway known for its dramatic coastal landscapes, rich fishing traditions, and excellent whale-watching opportunities.
  • 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: Fosen
Triple: [Trøndelag, hasSubregion, Fosen]
Generated description
Fosen is a peninsula and traditional district in central Norway known for its coastal landscape, wind farms, and location across the Trondheimsfjord from the city of Trondheim.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fosen
Target entity description: Fosen is a peninsula and traditional district in central Norway known for its coastal landscape, wind farms, and location across the Trondheimsfjord from the city of Trondheim.
  • A. Vestland
    Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
  • B. Lofoten
    Lofoten is a dramatic Arctic archipelago in Norway known for its steep mountains, sheltered bays, fishing villages, and views of the midnight sun and Northern Lights.
  • C. 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.
  • D. Troms
    Troms was a former county in northern Norway known for its Arctic landscapes, coastal fjords, and the city of Tromsø.
  • E. Vesterålen
    Vesterålen is a scenic archipelago in northern Norway known for its dramatic coastal landscapes, rich fishing traditions, and excellent whale-watching opportunities.
  • 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_69ac16f56bc0819094085d61f1f29f70 completed March 7, 2026, 12:15 p.m.
NEDg Description generation batch_69ac1841a6188190bca3ab98eb169d47 completed March 7, 2026, 12:21 p.m.
NED2 Entity disambiguation (via description) batch_69ac18afee148190ac7431327588c31b completed March 7, 2026, 12:23 p.m.
Created at: March 1, 2026, 7:38 p.m.