Triple

T22653330
Position Surface form Disambiguated ID Type / Status
Subject Bindal E559151 entity
Predicate countrySubdivision P766 FINISHED
Object Nordland NE NERFINISHED

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: Nordland | Statement: [Bindal, countrySubdivision, Nordland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nordland
Context triple: [Bindal, countrySubdivision, Nordland]
  • A. Nordland chosen
    Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic landscapes.
  • B. Nordlandet
    Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
  • C. Finnmark
    Finnmark is a sparsely populated, historically Norwegian region in the far northeast of Scandinavia, known for its Arctic climate, Sami culture, and dramatic coastal and tundra landscapes.
  • D. Hålogaland
    Hålogaland is a historical region in northern Norway traditionally encompassing parts of what are now Troms and Nordland counties.
  • E. Helgeland
    Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245489dd88190b1f674acf61c8769 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f17659e4dc81909cf6943c1c986ef9 completed April 29, 2026, 3:09 a.m.
Created at: April 17, 2026, 3:06 p.m.