Triple

T10398694
Position Surface form Disambiguated ID Type / Status
Subject Sirdal municipality E245086 entity
Predicate containsSettlement P847 FINISHED
Object Tjørhom
Tjørhom is a small village in southwestern Norway known for its mountainous landscape and proximity to popular skiing and outdoor recreation areas.
E861084 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: Tjørhom | Statement: [Sirdal municipality, containsSettlement, Tjørhom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tjørhom
Context triple: [Sirdal municipality, containsSettlement, Tjørhom]
  • A. Tingvoll
    Tingvoll is a small municipality and village area in western Norway known for its rural landscape, fjords, and agricultural traditions.
  • B. Suldal
    Suldal is a large rural municipality in southwestern Norway known for its fjords, mountains, and hydroelectric power production.
  • C. Gjerdrum
    Gjerdrum is a small rural municipality in Viken county, Norway, known for its agricultural landscape and proximity to the Oslo metropolitan area.
  • D. Ørskog
    Ørskog is a village and former municipality in western Norway, located in the county of Møre og Romsdal.
  • E. Bjerke
    Bjerke is a neighborhood in the Bjerke borough of Oslo, Norway, known primarily as a residential area with local services and amenities.
  • 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: Tjørhom
Triple: [Sirdal municipality, containsSettlement, Tjørhom]
Generated description
Tjørhom is a small village in southwestern Norway known for its mountainous landscape and proximity to popular skiing and outdoor recreation areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tjørhom
Target entity description: Tjørhom is a small village in southwestern Norway known for its mountainous landscape and proximity to popular skiing and outdoor recreation areas.
  • A. Tingvoll
    Tingvoll is a small municipality and village area in western Norway known for its rural landscape, fjords, and agricultural traditions.
  • B. Suldal
    Suldal is a large rural municipality in southwestern Norway known for its fjords, mountains, and hydroelectric power production.
  • C. Gjerdrum
    Gjerdrum is a small rural municipality in Viken county, Norway, known for its agricultural landscape and proximity to the Oslo metropolitan area.
  • D. Ørskog
    Ørskog is a village and former municipality in western Norway, located in the county of Møre og Romsdal.
  • E. Bjerke
    Bjerke is a neighborhood in the Bjerke borough of Oslo, Norway, known primarily as a residential area with local services and amenities.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9d1f2408190beaa8197641c66b4 completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fbc759a08190be677bf5458af0c8 completed April 9, 2026, 7:19 p.m.
NEDg Description generation batch_69d81c40dc6081908cc186ee6cd0814e completed April 9, 2026, 9:38 p.m.
NED2 Entity disambiguation (via description) batch_69d8277fbf0881908a1e16d6c07886e6 completed April 9, 2026, 10:26 p.m.
Created at: April 6, 2026, 12:07 p.m.