Triple

T10428892
Position Surface form Disambiguated ID Type / Status
Subject Flå E245856 entity
Predicate borders P224 FINISHED
Object Nes, Viken
Nes is a municipality in Viken county, Norway, known for its agricultural landscape and location along the Glomma River.
E861160 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: Nes, Viken | Statement: [Flå, borders, Nes, Viken]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nes, Viken
Context triple: [Flå, borders, Nes, Viken]
  • A. Vestlandet
    Vestlandet is the western region of Norway, known for its dramatic fjords, mountains, and coastal landscapes.
  • B. Nordre Land
    Nordre Land is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and agricultural landscape in the traditional district of Land.
  • C. Helgeland
    Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
  • D. Nordlandet
    Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
  • E. Jæren region
    The Jæren region is a coastal area in southwestern Norway known for its flat, fertile farmland, long sandy beaches, and the city of Stavanger as its main urban center.
  • 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: Nes, Viken
Triple: [Flå, borders, Nes, Viken]
Generated description
Nes is a municipality in Viken county, Norway, known for its agricultural landscape and location along the Glomma River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nes, Viken
Target entity description: Nes is a municipality in Viken county, Norway, known for its agricultural landscape and location along the Glomma River.
  • A. Vestlandet
    Vestlandet is the western region of Norway, known for its dramatic fjords, mountains, and coastal landscapes.
  • B. Nordre Land
    Nordre Land is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and agricultural landscape in the traditional district of Land.
  • C. Helgeland
    Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
  • D. Nordlandet
    Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
  • E. Jæren region
    The Jæren region is a coastal area in southwestern Norway known for its flat, fertile farmland, long sandy beaches, and the city of Stavanger as its main urban center.
  • 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_69d381bf3dc08190bf35a2643e4e8f22 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4ea4b4b5881908ae23f8efeea482b completed April 7, 2026, 11:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fc2d54048190b25f4d168a75ad3a completed April 9, 2026, 7:21 p.m.
NEDg Description generation batch_69d822d84e588190be199ad844d4f54d completed April 9, 2026, 10:06 p.m.
NED2 Entity disambiguation (via description) batch_69d8277fbf0881908a1e16d6c07886e6 completed April 9, 2026, 10:26 p.m.
Created at: April 6, 2026, 12:13 p.m.