Triple

T6426062
Position Surface form Disambiguated ID Type / Status
Subject Namdalen E128060 entity
Predicate namedAfter P63 FINISHED
Object Namsen
Namsen is a major river in Trøndelag county, Norway, renowned for its salmon fishing and central role in the Namdalen region.
E594747 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: Namsen | Statement: [Namdalen, namedAfter, Namsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namsen
Context triple: [Namdalen, namedAfter, Namsen]
  • A. Finnsnes
    Finnsnes is a small coastal town in northern Norway that serves as a commercial and transport hub for the island municipality of Senja.
  • B. Nesset
    Nesset is a former municipality in western Norway known for its scenic fjord landscapes and rural communities.
  • C. Namsenfjorden
    Namsenfjorden is a fjord in Trøndelag county, Norway, known for its scenic coastal landscape and connection to the Namsen River near the town of Namsos.
  • D. Rødberg
    Rødberg is a small village in southern Norway that serves as the administrative center of Nore og Uvdal municipality and a local hub for hydroelectric power production.
  • E. Hadsel
    Hadsel is a coastal municipality in Nordland county, Norway, known for encompassing several islands in the Vesterålen archipelago, including parts of Hadseløya, Langøya, and Austvågøya.
  • 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: Namsen
Triple: [Namdalen, namedAfter, Namsen]
Generated description
Namsen is a major river in Trøndelag county, Norway, renowned for its salmon fishing and central role in the Namdalen region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Namsen
Target entity description: Namsen is a major river in Trøndelag county, Norway, renowned for its salmon fishing and central role in the Namdalen region.
  • A. Finnsnes
    Finnsnes is a small coastal town in northern Norway that serves as a commercial and transport hub for the island municipality of Senja.
  • B. Nesset
    Nesset is a former municipality in western Norway known for its scenic fjord landscapes and rural communities.
  • C. Namsenfjorden
    Namsenfjorden is a fjord in Trøndelag county, Norway, known for its scenic coastal landscape and connection to the Namsen River near the town of Namsos.
  • D. Rødberg
    Rødberg is a small village in southern Norway that serves as the administrative center of Nore og Uvdal municipality and a local hub for hydroelectric power production.
  • E. Hadsel
    Hadsel is a coastal municipality in Nordland county, Norway, known for encompassing several islands in the Vesterålen archipelago, including parts of Hadseløya, Langøya, and Austvågøya.
  • 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_69c00838de888190af2eec0b80495efa completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0691f944c81909d4e5d8ef9e494b6 completed March 22, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64bbc865c81909bf064b9253bc263 completed March 27, 2026, 9:19 a.m.
NEDg Description generation batch_69c64e180f948190bbe69467c47c84e3 completed March 27, 2026, 9:30 a.m.
NED2 Entity disambiguation (via description) batch_69c64ead9b8c81908ba74c90057981a6 completed March 27, 2026, 9:32 a.m.
Created at: March 22, 2026, 4:43 p.m.