Triple

T5706958
Position Surface form Disambiguated ID Type / Status
Subject Oslo Airport Station E125807 entity
Predicate locatedIn P40 FINISHED
Object Greater 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: Greater Oslo Region | Statement: [Oslo Airport Station, locatedIn, Greater Oslo Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greater Oslo Region
Context triple: [Oslo Airport Station, locatedIn, Greater 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. Fredrikstad/Sarpsborg urban area
    The Fredrikstad/Sarpsborg urban area is a major contiguous metropolitan region in southeastern Norway that encompasses the twin cities of Fredrikstad and Sarpsborg.
  • 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. Østensjø district
    Østensjø district is a residential borough in the southeastern part of Oslo, Norway, known for its lakes, green spaces, and suburban character.
  • 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_69c0082d6fe48190b777fb383769e5c8 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024892fd88190a91133fc88365410 completed March 22, 2026, 5:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b0b3412c8190a4b97863e060e928 completed March 23, 2026, 3:17 a.m.
Created at: March 22, 2026, 3:45 p.m.