Triple

T1234747
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Law, University of Oslo E26521 entity
Predicate locatedIn P40 FINISHED
Object Oslo city centre E150936 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 city centre | Statement: [Faculty of Law, University of Oslo, locatedIn, Oslo city centre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oslo city centre
Context triple: [Faculty of Law, University of Oslo, locatedIn, Oslo city centre]
  • A. Sentrum, Oslo chosen
    Sentrum is the central borough of Oslo, Norway, encompassing the city’s main downtown area, key commercial districts, and major transport hubs.
  • B. Oslo
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • C. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • D. Bergen
    Bergen is Norway's second-largest city, renowned for its historic harbor, surrounding mountains and fjords, and role as a former Hanseatic trading hub.
  • E. Kolsås
    Kolsås is a suburban area in Bærum, Norway, known as the endpoint of one of the Oslo Metro lines and for its nearby forested hill popular for hiking and climbing.
  • 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_69a4be5e421081908f2432528019db25 completed March 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae30355a548190af3f858170b9b82c completed March 9, 2026, 2:28 a.m.
Created at: March 1, 2026, 7:47 p.m.