Triple

T6082408
Position Surface form Disambiguated ID Type / Status
Subject Drammen Line E135553 entity
Predicate passesThrough P225 FINISHED
Object Asker E125781 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: [Drammen Line, passesThrough, Asker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asker
Context triple: [Drammen Line, passesThrough, Asker]
  • A. Asker chosen
    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 municipal council
    Asker municipal council is the elected local governing body responsible for making political and administrative decisions for the municipality of Asker in Norway.
  • E. Andselv
    Andselv is a small Norwegian village located in the Troms region, known for its position along the Andselva river and proximity to Bardufoss.
  • 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_69c0087ad31c8190ab936e0ff28614b6 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05786233c81909010a6c2f7e7dfda completed March 22, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11d57b5f481908d7df374837a486a completed March 23, 2026, 11 a.m.
Created at: March 22, 2026, 4:11 p.m.