Triple

T5663146
Position Surface form Disambiguated ID Type / Status
Subject Bjørnstjerne Bjørnson E124792 entity
Predicate placeOfBirth P1 FINISHED
Object 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.
 E549188 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: Kvikne | Statement: [Bjørnstjerne Bjørnson, placeOfBirth, Kvikne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kvikne
Context triple: [Bjørnstjerne Bjørnson, placeOfBirth, Kvikne]
  • A. Kvænangen
    Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
  • B. Bjugn
    Bjugn is a former municipality and coastal community in Trøndelag county, Norway, known for its fishing, agriculture, and location on the Fosen peninsula.
  • C. Evenskjer
    Evenskjer is a small village in Northern Norway that serves as an administrative and service center in the Troms region.
  • D. Bremsnes
    Bremsnes is a village on the island of Averøya in Møre og Romsdal county, Norway, known for its coastal setting and local church.
  • E. Fosnes
    Fosnes was a former rural municipality in Trøndelag county, Norway, known for its coastal landscape and small, dispersed population.
  • 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: Kvikne
Triple: [Bjørnstjerne Bjørnson, placeOfBirth, Kvikne]
Generated description
Kvikne is a rural village area in central Norway, known historically for mining and as the birthplace of Nobel Prize–winning writer Bjørnstjerne Bjørnson.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kvikne
Target entity description: Kvikne is a rural village area in central Norway, known historically for mining and as the birthplace of Nobel Prize–winning writer Bjørnstjerne Bjørnson.
  • A. Kvænangen
    Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
  • B. Bjugn
    Bjugn is a former municipality and coastal community in Trøndelag county, Norway, known for its fishing, agriculture, and location on the Fosen peninsula.
  • C. Evenskjer
    Evenskjer is a small village in Northern Norway that serves as an administrative and service center in the Troms region.
  • D. Bremsnes
    Bremsnes is a village on the island of Averøya in Møre og Romsdal county, Norway, known for its coastal setting and local church.
  • E. Fosnes
    Fosnes was a former rural municipality in Trøndelag county, Norway, known for its coastal landscape and small, dispersed population.
  • 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_69c00828906881908966f270b8f130cf completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023232e6481909b2a0456d240fe8e completed March 22, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c097d7e0fc81909f051f8789ef9fb9 completed March 23, 2026, 1:31 a.m.
NEDg Description generation batch_69c0989f7e58819098175e6eaacdb9ee completed March 23, 2026, 1:34 a.m.
NED2 Entity disambiguation (via description) batch_69c09cf3220481908c52b519e8495fff completed March 23, 2026, 1:52 a.m.
Created at: March 22, 2026, 3:43 p.m.