Triple

T10450627
Position Surface form Disambiguated ID Type / Status
Subject Akershus county E246411 entity
Predicate hadMunicipality P84684 FINISHED
Object Skedsmo E182120 NE FINISHED

How this triple was built (2 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: Skedsmo | Statement: [Akershus county, hadMunicipality, Skedsmo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skedsmo
Context triple: [Akershus county, hadMunicipality, Skedsmo]
  • A. Skedsmo chosen
    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. Bjerkreim
    Bjerkreim is a rural municipality in southwestern Norway known for its rivers, salmon fishing, and agricultural landscape.
  • D. Trysil
    Trysil is a Norwegian municipality renowned for its large alpine ski resort and extensive outdoor recreation opportunities.
  • E. Skøyen
    Skøyen is a neighborhood in western Oslo, Norway, known as a busy residential and commercial hub with strong public transport connections.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d381c04fe08190957c26c526a3b05a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5190da7f081908c38b5964a567e37 completed April 7, 2026, 2:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69e37382a0bc81908938b3cbdf0528e0 completed April 18, 2026, 12:05 p.m.
Created at: April 6, 2026, 12:17 p.m.