Triple

T11357951
Position Surface form Disambiguated ID Type / Status
Subject Vidkun Quisling E269010 entity
Predicate placeOfBirth P1 FINISHED
Object Fyresdal
Fyresdal is a rural municipality in Telemark county, Norway, known for its forests, lakes, and traditional farming communities.
E920939 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: Fyresdal | Statement: [Vidkun Quisling, placeOfBirth, Fyresdal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fyresdal
Context triple: [Vidkun Quisling, placeOfBirth, Fyresdal]
  • A. Fagernes
    Fagernes is a small town in central Norway that serves as a regional hub and gateway to the mountainous Valdres district.
  • B. Flesberg
    Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
  • C. Valldal
    Valldal is a village in western Norway known for its scenic fjord landscape and strawberry farming, situated in the county of Møre og Romsdal.
  • D. Fosnes
    Fosnes was a former rural municipality in Trøndelag county, Norway, known for its coastal landscape and small, dispersed population.
  • 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: Fyresdal
Triple: [Vidkun Quisling, placeOfBirth, Fyresdal]
Generated description
Fyresdal is a rural municipality in Telemark county, Norway, known for its forests, lakes, and traditional farming communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Fyresdal
Target entity description: Fyresdal is a rural municipality in Telemark county, Norway, known for its forests, lakes, and traditional farming communities.
  • A. Fagernes
    Fagernes is a small town in central Norway that serves as a regional hub and gateway to the mountainous Valdres district.
  • B. Flesberg
    Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
  • C. Valldal
    Valldal is a village in western Norway known for its scenic fjord landscape and strawberry farming, situated in the county of Møre og Romsdal.
  • D. Fosnes
    Fosnes was a former rural municipality in Trøndelag county, Norway, known for its coastal landscape and small, dispersed population.
  • 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_69d6aacbe18081909e5fadb50082dd96 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea419afc8190b3a93141d015ebdf completed April 9, 2026, 6:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69e543bdd6d88190b4f816ffde5179be completed April 19, 2026, 9:06 p.m.
NEDg Description generation batch_69e5474b77948190b2c45831871383e8 completed April 19, 2026, 9:21 p.m.
NED2 Entity disambiguation (via description) batch_69e54efda820819092d6a94fa4fd21f0 completed April 19, 2026, 9:54 p.m.
Created at: April 8, 2026, 9:33 p.m.