Triple

T4365576
Position Surface form Disambiguated ID Type / Status
Subject Oppland E98763 entity
Predicate containsPart P35 FINISHED
Object Nord-Fron
Nord-Fron is a rural municipality in Innlandet county, Norway, known for its mountainous landscapes, traditional farming communities, and location in the Gudbrandsdalen valley.
 E433529 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: Nord-Fron | Statement: [Oppland, containsPart, Nord-Fron]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nord-Fron
Context triple: [Oppland, containsPart, Nord-Fron]
  • A. Nordlandet
    Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
  • B. Romsdal
    Romsdal is a traditional district in Møre og Romsdal county in western Norway, known for its dramatic fjords, mountains, and the town of Molde.
  • C. Nordland
    Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic landscapes.
  • D. Helgeland
    Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
  • E. Hadeland
    Hadeland is a traditional rural district in southeastern Norway known for its agricultural landscape, historic churches, and the Hadeland Glassverk glassworks.
  • 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: Nord-Fron
Triple: [Oppland, containsPart, Nord-Fron]
Generated description
Nord-Fron is a rural municipality in Innlandet county, Norway, known for its mountainous landscapes, traditional farming communities, and location in the Gudbrandsdalen valley.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nord-Fron
Target entity description: Nord-Fron is a rural municipality in Innlandet county, Norway, known for its mountainous landscapes, traditional farming communities, and location in the Gudbrandsdalen valley.
  • A. Nordlandet
    Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
  • B. Romsdal
    Romsdal is a traditional district in Møre og Romsdal county in western Norway, known for its dramatic fjords, mountains, and the town of Molde.
  • C. Nordland
    Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic landscapes.
  • D. Helgeland
    Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
  • E. Hadeland
    Hadeland is a traditional rural district in southeastern Norway known for its agricultural landscape, historic churches, and the Hadeland Glassverk glassworks.
  • 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_69b3454c772081908e20173e379e8ebe completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35200263081909bb326a4d7a8db99 completed March 12, 2026, 11:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5dbcbbd1881908eb9f0ea6b2fe16b completed March 14, 2026, 10:06 p.m.
NEDg Description generation batch_69b5dcf36dfc8190847925dbed92c059 completed March 14, 2026, 10:10 p.m.
NED2 Entity disambiguation (via description) batch_69b5ddad45b8819082ac7a3a9c5f2f07 completed March 14, 2026, 10:14 p.m.
Created at: March 12, 2026, 11:17 p.m.