Triple

T10428522
Position Surface form Disambiguated ID Type / Status
Subject Skiptvet E245847 entity
Predicate hasAdministrativeCentre P1474 FINISHED
Object Meieribyen
Meieribyen is a village in Viken county, Norway, serving as the main local center of administration and services for the surrounding Skiptvet municipality.
 E866580 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: Meieribyen | Statement: [Skiptvet, hasAdministrativeCentre, Meieribyen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Meieribyen
Context triple: [Skiptvet, hasAdministrativeCentre, Meieribyen]
  • A. Teigebyen
    Teigebyen is a village in Viken county, Norway, serving as the main local hub for municipal services and community life in Nannestad.
  • B. Bjerke
    Bjerke is a neighborhood in the Bjerke borough of Oslo, Norway, known primarily as a residential area with local services and amenities.
  • C. Bremsnes
    Bremsnes is a village on the island of Averøya in Møre og Romsdal county, Norway, known for its coastal setting and local church.
  • D. Kvænangen
    Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
  • E. Nadderud
    Nadderud is a residential and sports-focused area in Bærum, Norway, known for its stadium and athletic facilities.
  • 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: Meieribyen
Triple: [Skiptvet, hasAdministrativeCentre, Meieribyen]
Generated description
Meieribyen is a village in Viken county, Norway, serving as the main local center of administration and services for the surrounding Skiptvet municipality.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Meieribyen
Target entity description: Meieribyen is a village in Viken county, Norway, serving as the main local center of administration and services for the surrounding Skiptvet municipality.
  • A. Teigebyen
    Teigebyen is a village in Viken county, Norway, serving as the main local hub for municipal services and community life in Nannestad.
  • B. Bjerke
    Bjerke is a neighborhood in the Bjerke borough of Oslo, Norway, known primarily as a residential area with local services and amenities.
  • C. Bremsnes
    Bremsnes is a village on the island of Averøya in Møre og Romsdal county, Norway, known for its coastal setting and local church.
  • D. Kvænangen
    Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
  • E. Nadderud
    Nadderud is a residential and sports-focused area in Bærum, Norway, known for its stadium and athletic facilities.
  • 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_69d381bf3dc08190bf35a2643e4e8f22 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4ea4a7dcc81909a830e08656a1c0c completed April 7, 2026, 11:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69d8dc374f6c8190a44b9da27be343e4 completed April 10, 2026, 11:17 a.m.
NEDg Description generation batch_69d8e8c683608190aa4333ed38e79f53 completed April 10, 2026, 12:10 p.m.
NED2 Entity disambiguation (via description) batch_69d901c7684c8190837ed9ef0c2428af completed April 10, 2026, 1:57 p.m.
Created at: April 6, 2026, 12:13 p.m.