Triple

T1229351
Position Surface form Disambiguated ID Type / Status
Subject Sentrum E26400 entity
Predicate contains P35 FINISHED
Object Oslo Central Station E22609 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 Central Station | Statement: [Sentrum, contains, Oslo Central Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oslo Central Station
Context triple: [Sentrum, contains, Oslo Central Station]
  • A. Oslo Central Station chosen
    Oslo Central Station is Norway’s largest and busiest railway hub, serving as the main national and regional train terminal in the heart of Oslo.
  • B. Oslo Airport Station
    Oslo Airport Station is the main railway station serving Oslo Airport, Gardermoen, providing high-speed and regional train connections between the airport and the rest of Norway.
  • C. Oslo Bus Terminal
    Oslo Bus Terminal is the main long-distance and regional bus hub in Oslo, Norway, connecting the city with domestic and international destinations.
  • D. Stortinget metro station
    Stortinget metro station is a central underground station in Oslo’s metro system, serving as a major hub for lines running through the city center.
  • E. Oslo City Hall
    Oslo City Hall is a prominent civic building and cultural landmark in Norway’s capital, known for hosting the Nobel Peace Prize ceremony and featuring distinctive brick architecture and rich interior artworks.
  • 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_69a4948571c88190a9191e451e6035fd completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be3dac2c8190914ff27173bb6b34 completed March 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8f7391408190928cab62e34aa361 completed March 7, 2026, 8:49 p.m.
Created at: March 1, 2026, 7:47 p.m.