Triple

T2912286
Position Surface form Disambiguated ID Type / Status
Subject Froland E63709 entity
Predicate hasSettlement P1068 FINISHED
Object Mjølhus
Mjølhus is a small settlement located within the municipality of Froland in Agder county, Norway.
E308949 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: Mjølhus | Statement: [Froland, hasSettlement, Mjølhus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mjølhus
Context triple: [Froland, hasSettlement, Mjølhus]
  • A. Skedsmo
    Skedsmo is a former municipality in Viken county, Norway, located northeast of Oslo and known for its suburban communities and historical ties to the Oslo region.
  • B. Mortensrud
    Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
  • C. Vikingsholm
    Vikingsholm is a historic Scandinavian-style stone mansion and former summer home located on the shores of Emerald Bay at Lake Tahoe in California.
  • D. Vegårshei
    Vegårshei is a rural municipality in Agder county in southern Norway, known for its forests, lakes, and traditional inland communities.
  • E. St. Hanshaugen
    St. Hanshaugen is a central borough of Oslo, Norway, known for its large hillside park and vibrant urban residential areas.
  • 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: Mjølhus
Triple: [Froland, hasSettlement, Mjølhus]
Generated description
Mjølhus is a small settlement located within the municipality of Froland in Agder county, Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mjølhus
Target entity description: Mjølhus is a small settlement located within the municipality of Froland in Agder county, Norway.
  • A. Skedsmo
    Skedsmo is a former municipality in Viken county, Norway, located northeast of Oslo and known for its suburban communities and historical ties to the Oslo region.
  • B. Mortensrud
    Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
  • C. Vikingsholm
    Vikingsholm is a historic Scandinavian-style stone mansion and former summer home located on the shores of Emerald Bay at Lake Tahoe in California.
  • D. Vegårshei
    Vegårshei is a rural municipality in Agder county in southern Norway, known for its forests, lakes, and traditional inland communities.
  • E. St. Hanshaugen
    St. Hanshaugen is a central borough of Oslo, Norway, known for its large hillside park and vibrant urban residential areas.
  • 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_69ab4c44ab448190b9411324e8a1fc1d completed March 6, 2026, 9:51 p.m.
NER Named-entity recognition batch_69abe0eb77708190b745b887f3b9a618 completed March 7, 2026, 8:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0562014fc8190b7b702fa40682382 completed March 10, 2026, 5:34 p.m.
NEDg Description generation batch_69b05f7e78e8819095185f170ca26bda completed March 10, 2026, 6:14 p.m.
NED2 Entity disambiguation (via description) batch_69b0617a21a881909a0f52268a2494a6 completed March 10, 2026, 6:22 p.m.
Created at: March 6, 2026, 10:11 p.m.