Triple

T591292
Position Surface form Disambiguated ID Type / Status
Subject Western Norway E17275 entity
Predicate largestCity P235 FINISHED
Object Bergen 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 | Statement: [Western Norway, largestCity, Bergen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bergen
Context triple: [Western Norway, largestCity, Bergen]
  • A. 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.
  • B. 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.
  • C. Oslo
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • D. Ålesund
    Ålesund is a coastal Norwegian city renowned for its distinctive Art Nouveau architecture and location across several islands in Western Norway.
  • E. Tromsø
    Tromsø is a city in northern Norway known for its Arctic location, vibrant cultural scene, and prominence as a viewing spot for the Northern Lights.
  • 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_69a49379d09c8190ac7e00b24e2810b1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49bbaf53081908eed240bed09f63b completed March 1, 2026, 8:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69a52ea8dd8481909108a8873c5d49d5 completed March 2, 2026, 6:31 a.m.
Created at: March 1, 2026, 7:33 p.m.