Triple

T9517695
Position Surface form Disambiguated ID Type / Status
Subject Greater Oslo Region E229565 entity
Predicate contains P35 FINISHED
Object Asker E575307 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: Asker | Statement: [Greater Oslo Region, contains, Asker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asker
Context triple: [Greater Oslo Region, contains, Asker]
  • A. Asker
    Asker is a municipality in Viken county, Norway, known for its coastal location near Oslo and its mix of residential areas, cultural sites, and natural landscapes.
  • B. Askeran
    Askeran is a town in the disputed Nagorno-Karabakh region of the South Caucasus, historically known for its strategic location and fortress.
  • C. Aske
    Aske is a surname of Scandinavian origin borne by various individuals, including those with the given name Ellen.
  • D. Asker municipality
    Asker municipality is a local government area in Viken county, Norway, known as a suburban region west of Oslo that includes several affluent residential areas and royal estates.
  • E. Asker, Norway chosen
    Asker, Norway is a suburban municipality southwest of Oslo known for its affluent residential areas, coastal landscapes along the Oslofjord, and role as home to members of the Norwegian royal family.
  • 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_69ca84777560819084cddd999badc1aa completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9880417c819097dde277988df36d completed April 1, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69d13a4aeb008190ae5d54367efe2722 completed April 4, 2026, 4:20 p.m.
Created at: March 30, 2026, 7:59 p.m.