Triple

T7236343
Position Surface form Disambiguated ID Type / Status
Subject Ivar Giaever E155236 entity
Predicate placeOfBirth P1 FINISHED
Object Bergen, Norway E74082 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: Bergen, Norway | Statement: [Ivar Giaever, placeOfBirth, Bergen, Norway]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bergen, Norway
Context triple: [Ivar Giaever, placeOfBirth, Bergen, Norway]
  • A. Bergen
    Bergen is a city in western Germany, historically notable as the site of the 1759 Battle of Bergen during the Seven Years' War.
  • B. Bergen chosen
    Bergen is Norway's second-largest city, renowned for its historic harbor, surrounding mountains and fjords, and role as a former Hanseatic trading hub.
  • C. Bergens
    The Bergens are a race of gloomy, troll-eating creatures who serve as the primary villains in the animated film "Trolls."
  • D. Fornebu, Norway
    Fornebu, Norway is a coastal area in Bærum just outside Oslo, known for its transformation from the city’s former main airport into a modern hub for technology companies, offices, and residential developments.
  • E. Stavanger
    Stavanger is a coastal city in southwestern Norway known for its oil industry hub status, historic wooden houses, and proximity to natural attractions like the Lysefjord and Preikestolen.
  • 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_69c688143bfc81908d4176617735e601 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ea33dd3481908ebb050e1fab5aaa completed March 27, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8ac7b53488190a00978e936b563ac completed March 29, 2026, 4:37 a.m.
Created at: March 27, 2026, 2:55 p.m.