Triple

T20707921
Position Surface form Disambiguated ID Type / Status
Subject Class 71 electric multiple unit E508952 entity
Predicate operatingArea P82 FINISHED
Object Oslo region NE NERFINISHED

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: Oslo region | Statement: [Class 71 electric multiple unit, operatingArea, Oslo region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oslo region
Context triple: [Class 71 electric multiple unit, operatingArea, Oslo region]
  • A. Bergen region
    The Bergen region is a coastal metropolitan area in western Norway centered on the city of Bergen and its surrounding islands and municipalities.
  • B. Greater Oslo Region chosen
    The Greater Oslo Region is the metropolitan area surrounding Norway’s capital, encompassing Oslo and its neighboring municipalities as a unified economic and commuter region.
  • C. Drammensregionen
    Drammensregionen is a metropolitan area in southeastern Norway centered around the city of Drammen and its surrounding municipalities.
  • D. Oslo county
    Oslo county is Norway’s capital county, encompassing the city of Oslo and serving as the country’s political, economic, and cultural center.
  • E. Gjøvik Region
    Gjøvik Region is a regional area in Innlandet county, Norway, centered around the town of Gjøvik and its surrounding municipalities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4c40ad88190b81f77695366d328 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c1952e888190877b79933970f7b0 completed April 21, 2026, 12:15 a.m.
Created at: April 16, 2026, 12:14 p.m.