Triple

T13808259
Position Surface form Disambiguated ID Type / Status
Subject Gran municipality E331814 entity
Predicate contains P35 FINISHED
Object Røykenvik
Røykenvik is a small village and former railway terminus located by Randsfjorden in Gran municipality in Innlandet county, Norway.
E1090087 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: Røykenvik | Statement: [Gran municipality, contains, Røykenvik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Røykenvik
Context triple: [Gran municipality, contains, Røykenvik]
  • A. Røyrvik
    Røyrvik is a small rural municipality in Trøndelag county, Norway, known for its mountainous landscapes, reindeer herding traditions, and proximity to Børgefjell National Park.
  • B. Klemetsrud
    Klemetsrud is a residential area and neighborhood in the Søndre Nordstrand borough of Oslo, Norway.
  • C. Brårud
    Brårud is a small village located within the municipality of Nes in Akershus county, Norway.
  • D. Kvikne
    Kvikne is a rural village area in central Norway, known historically for mining and as the birthplace of Nobel Prize–winning writer Bjørnstjerne Bjørnson.
  • E. Nissedal
    Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation 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: Røykenvik
Triple: [Gran municipality, contains, Røykenvik]
Generated description
Røykenvik is a small village and former railway terminus located by Randsfjorden in Gran municipality in Innlandet county, Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Røykenvik
Target entity description: Røykenvik is a small village and former railway terminus located by Randsfjorden in Gran municipality in Innlandet county, Norway.
  • A. Røyrvik
    Røyrvik is a small rural municipality in Trøndelag county, Norway, known for its mountainous landscapes, reindeer herding traditions, and proximity to Børgefjell National Park.
  • B. Klemetsrud
    Klemetsrud is a residential area and neighborhood in the Søndre Nordstrand borough of Oslo, Norway.
  • C. Brårud
    Brårud is a small village located within the municipality of Nes in Akershus county, Norway.
  • D. Kvikne
    Kvikne is a rural village area in central Norway, known historically for mining and as the birthplace of Nobel Prize–winning writer Bjørnstjerne Bjørnson.
  • E. Nissedal
    Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation 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_69d81c59f8808190a851bc56afdc55e9 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de026eae8481908b8880635e6a9152 completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd323be8d48190b0b289f25de06fb1 completed May 8, 2026, 12:45 a.m.
NEDg Description generation batch_69fd366ca0a88190a93ba290c56ee220 completed May 8, 2026, 1:03 a.m.
NED2 Entity disambiguation (via description) batch_69fd377b46788190a06d7f41aa37a9f5 completed May 8, 2026, 1:08 a.m.
Created at: April 9, 2026, 10:12 p.m.