Triple

T10428408
Position Surface form Disambiguated ID Type / Status
Subject Nes (Akershus) E245844 entity
Predicate hasSettlement P1068 FINISHED
Object Oppåkermoen
Oppåkermoen is a small village located in the municipality of Nes in Akershus county, Norway.
E864939 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: Oppåkermoen | Statement: [Nes (Akershus), hasSettlement, Oppåkermoen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oppåkermoen
Context triple: [Nes (Akershus), hasSettlement, Oppåkermoen]
  • A. Jørstadmoen
    Jørstadmoen is a military base and village area in Lillehammer, Norway, known primarily as a key site for the Norwegian Armed Forces and home to important defense and cyber units.
  • B. Møysalen
    Møysalen is a prominent mountain in northern Norway known for its rugged alpine scenery and popular hiking routes.
  • C. Ullernåsen
    Ullernåsen is a residential hillside neighborhood in Oslo, Norway, known for its apartment blocks, green surroundings, and views over the western parts of the city.
  • D. Glåma
    Glåma is the longest and largest river in Norway, flowing through eastern parts of the country before emptying into the Oslofjord.
  • E. Sørreisa
    Sørreisa is a small coastal municipality and village area in northern Norway known for its fjords and rural Arctic landscape.
  • 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: Oppåkermoen
Triple: [Nes (Akershus), hasSettlement, Oppåkermoen]
Generated description
Oppåkermoen is a small village located in the municipality of Nes in Akershus county, Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Oppåkermoen
Target entity description: Oppåkermoen is a small village located in the municipality of Nes in Akershus county, Norway.
  • A. Jørstadmoen
    Jørstadmoen is a military base and village area in Lillehammer, Norway, known primarily as a key site for the Norwegian Armed Forces and home to important defense and cyber units.
  • B. Møysalen
    Møysalen is a prominent mountain in northern Norway known for its rugged alpine scenery and popular hiking routes.
  • C. Ullernåsen
    Ullernåsen is a residential hillside neighborhood in Oslo, Norway, known for its apartment blocks, green surroundings, and views over the western parts of the city.
  • D. Glåma
    Glåma is the longest and largest river in Norway, flowing through eastern parts of the country before emptying into the Oslofjord.
  • E. Sørreisa
    Sørreisa is a small coastal municipality and village area in northern Norway known for its fjords and rural Arctic landscape.
  • 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_69d89f8a5b00819080c303bb0fc82f5a completed April 10, 2026, 6:58 a.m.
NEDg Description generation batch_69d8a1656b348190ba932d03402d6a4d completed April 10, 2026, 7:06 a.m.
NED2 Entity disambiguation (via description) batch_69d8a2b82bb48190899f37a967fef444 completed April 10, 2026, 7:11 a.m.
Created at: April 6, 2026, 12:13 p.m.