Triple

T12915243
Position Surface form Disambiguated ID Type / Status
Subject Royal Norwegian Society of Sciences and Letters E308962 entity
Predicate headquartersLocation P62 FINISHED
Object Trondheim E136993 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: Trondheim | Statement: [Royal Norwegian Society of Sciences and Letters, headquartersLocation, Trondheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trondheim
Context triple: [Royal Norwegian Society of Sciences and Letters, 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 (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_69d7bdf92b588190acdf2a2291ac4590 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d971a0d6508190bca9668e9e06abfe completed April 10, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f73051273c81909eb91c923f37557e completed May 3, 2026, 11:24 a.m.
Created at: April 9, 2026, 5:41 p.m.