Triple

T3624124
Position Surface form Disambiguated ID Type / Status
Subject Candice Bergen E76795 entity
Predicate familyName P18 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: [Candice Bergen, familyName, Bergen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bergen
Context triple: [Candice Bergen, familyName, 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. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • C. 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.
  • D. Oslo
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • E. Kristiansand
    Kristiansand is a coastal city in southern Norway known for its harbor, beaches, and role as a regional cultural and economic center.
  • 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_69ad85dc03948190b35b7189e4175bcc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc2d9845c8190ad65b2471000dfa0 completed March 8, 2026, 6:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69b589b716648190aeaead138203cbf9 completed March 14, 2026, 4:15 p.m.
Created at: March 8, 2026, 3:23 p.m.