Triple

T20745724
Position Surface form Disambiguated ID Type / Status
Subject Norwegian Courts Administration E510577 entity
Predicate headquartersLocation P62 FINISHED
Object Trondheim NE NERFINISHED

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: Trondheim | Statement: [Norwegian Courts Administration, headquartersLocation, Trondheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trondheim
Context triple: [Norwegian Courts Administration, headquartersLocation, Trondheim]
  • A. Trondheim chosen
    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
    Oslo is a collection of shared libraries that provide common code and patterns used across various OpenStack projects.
  • C. Oslo
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • 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. Bergen
    Bergen is a city in western Germany, historically notable as the site of the 1759 Battle of Bergen during the Seven Years' War.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4c845e88190b4c5f3ae79291182 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c212b744819089bc1d47a020bd61 completed April 21, 2026, 12:17 a.m.
Created at: April 16, 2026, 12:33 p.m.