Triple

T15054788
Position Surface form Disambiguated ID Type / Status
Subject Elisiv of Kiev E379460 entity
Predicate residence P75 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: [Elisiv of Kiev, residence, Trondheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trondheim
Context triple: [Elisiv of Kiev, residence, 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 the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • C. Oslo
    Oslo is a collection of shared libraries that provide common code and patterns used across various OpenStack projects.
  • 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_69d85cd64d108190853797a95c11cc45 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69deda92091c81909180f486edf01405 completed April 15, 2026, 12:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69feb7dd767c8190a129f00303f970bc completed May 9, 2026, 4:28 a.m.
Created at: April 10, 2026, 3:01 a.m.