Triple

T10428320
Position Surface form Disambiguated ID Type / Status
Subject Nannestad E245842 entity
Predicate hasSettlement P1068 FINISHED
Object Eltonåsen
Eltonåsen is a village in Nannestad municipality in Viken county, Norway, known as a small residential community within commuting distance of Oslo.
E862688 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: Eltonåsen | Statement: [Nannestad, hasSettlement, Eltonåsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eltonåsen
Context triple: [Nannestad, hasSettlement, Eltonåsen]
  • A. Lysthaugen
    Lysthaugen is a small settlement located in the municipality of Verdal in Trøndelag county, Norway.
  • B. Ormåsen
    Ormåsen is a small residential village in Øvre Eiker municipality in Buskerud county, Norway.
  • C. 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.
  • D. Holtålen
    Holtålen is a rural municipality in Trøndelag county, Norway, known for its valleys, rivers, and traditional farming and forestry.
  • E. Hisingen
    Hisingen is a large island and district in Gothenburg, Sweden, known for its industrial areas, shipyards, and rapidly developing residential and tech hubs.
  • 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: Eltonåsen
Triple: [Nannestad, hasSettlement, Eltonåsen]
Generated description
Eltonåsen is a village in Nannestad municipality in Viken county, Norway, known as a small residential community within commuting distance of Oslo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Eltonåsen
Target entity description: Eltonåsen is a village in Nannestad municipality in Viken county, Norway, known as a small residential community within commuting distance of Oslo.
  • A. Lysthaugen
    Lysthaugen is a small settlement located in the municipality of Verdal in Trøndelag county, Norway.
  • B. Ormåsen
    Ormåsen is a small residential village in Øvre Eiker municipality in Buskerud county, Norway.
  • C. 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.
  • D. Holtålen
    Holtålen is a rural municipality in Trøndelag county, Norway, known for its valleys, rivers, and traditional farming and forestry.
  • E. Hisingen
    Hisingen is a large island and district in Gothenburg, Sweden, known for its industrial areas, shipyards, and rapidly developing residential and tech hubs.
  • 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_69d7fc2d54048190b25f4d168a75ad3a completed April 9, 2026, 7:21 p.m.
NEDg Description generation batch_69d822d76f3481909f7c04be19414b14 completed April 9, 2026, 10:06 p.m.
NED2 Entity disambiguation (via description) batch_69d85a00e7f48190bf87ce9d04acc750 completed April 10, 2026, 2:01 a.m.
Created at: April 6, 2026, 12:13 p.m.