Triple

T5575971
Position Surface form Disambiguated ID Type / Status
Subject Brian Helgeland E146319 entity
Predicate familyName P18 FINISHED
Object Helgeland E388787 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: Helgeland | Statement: [Brian Helgeland, familyName, Helgeland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helgeland
Context triple: [Brian Helgeland, familyName, Helgeland]
  • A. Helgeland chosen
    Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
  • B. Nordlandet
    Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
  • C. Nordland
    Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic landscapes.
  • D. Nordre Land
    Nordre Land is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and agricultural landscape in the traditional district of Land.
  • E. Hadeland
    Hadeland is a traditional rural district in southeastern Norway known for its agricultural landscape, historic churches, and the Hadeland Glassverk glassworks.
  • 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_69c008ffed108190a084602227af6157 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c02067e8d8819090a006cb266da5fe completed March 22, 2026, 5:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d21ac6c81908a07c049d1ab81c6 completed March 22, 2026, 8:12 p.m.
Created at: March 22, 2026, 3:37 p.m.