Triple

T2206777
Position Surface form Disambiguated ID Type / Status
Subject Viken county E50816 entity
Predicate borders P224 FINISHED
Object Innlandet county E65742 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: Innlandet county | Statement: [Viken county, borders, Innlandet county]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Innlandet county
Context triple: [Viken county, borders, Innlandet county]
  • A. Oslo County
    Oslo County is the administrative region that encompasses Norway’s capital city, Oslo, serving as a central hub for the country’s political, cultural, and academic institutions.
  • B. Viken county
    Viken county is an administrative region in southeastern Norway that includes several municipalities and borders Sweden and the Oslofjord.
  • C. Oppland
    Oppland is a former inland county in southeastern Norway known for its mountainous terrain, national parks, and popular skiing and hiking areas.
  • D. Kronoberg County
    Kronoberg County is an administrative region in southern Sweden, largely covering parts of the historical province of Småland and known for its forests, lakes, and glassmaking tradition.
  • E. Innlandet chosen
    Innlandet is a county in eastern Norway known for its inland landscapes, including mountains, forests, and important winter sports venues.
  • 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_69a88b06709c8190978fb2418470d1b6 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abbfca300c81908b33debafa77d152 completed March 7, 2026, 6:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae654b89b081908f8c8b9bfc0b6579 completed March 9, 2026, 6:14 a.m.
Created at: March 4, 2026, 7:46 p.m.