Triple

T1139668
Position Surface form Disambiguated ID Type / Status
Subject Oslo Tramway E23420 entity
Predicate locatedIn P40 FINISHED
Object Oslo og Viken urban area E3654 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 og Viken urban area | Statement: [Oslo Tramway, locatedIn, Oslo og Viken urban area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oslo og Viken urban area
Context triple: [Oslo Tramway, locatedIn, Oslo og Viken urban area]
  • A. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • B. 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.
  • C. Østensjø district
    Østensjø district is a residential borough in the southeastern part of Oslo, Norway, known for its lakes, green spaces, and suburban character.
  • D. Oslo chosen
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • E. 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.
  • 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_69a493ef399c8190b04b9146d2314f59 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc27c88881909c64ec30b7f66575 completed March 1, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69adeab57c8c81908b1dbdaf7ba4b29b completed March 8, 2026, 9:31 p.m.
Created at: March 1, 2026, 7:44 p.m.