Triple

T7287392
Position Surface form Disambiguated ID Type / Status
Subject Oslo University Hospital Rikshospitalet E163907 entity
Predicate serves P98 FINISHED
Object Oslo region E229565 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: Oslo region | Statement: [Oslo University Hospital Rikshospitalet, serves, Oslo region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oslo region
Context triple: [Oslo University Hospital Rikshospitalet, serves, Oslo region]
  • A. 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.
  • B. Drammensregionen
    Drammensregionen is a metropolitan area in southeastern Norway centered around the city of Drammen and its surrounding municipalities.
  • C. 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.
  • D. Gjøvik Region
    Gjøvik Region is a regional area in Innlandet county, Norway, centered around the town of Gjøvik and its surrounding municipalities.
  • E. Lillehammer region
    The Lillehammer region is an area in southeastern Norway known for its winter sports facilities, scenic landscapes, and role as host of the 1994 Winter Olympics.
  • 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_69c6886093b88190a254b1ce6db8bae7 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eb6a73fc8190ae5ce81fd3e46d87 completed March 27, 2026, 8:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8e56e62d48190b0e25464ebffe148 completed March 29, 2026, 8:40 a.m.
Created at: March 27, 2026, 2:59 p.m.