Triple

T17143675
Position Surface form Disambiguated ID Type / Status
Subject Jämtland County E416033 entity
Predicate borderedBy P224 FINISHED
Object Trøndelag County E910948 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: Trøndelag County | Statement: [Jämtland County, borderedBy, Trøndelag County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trøndelag County
Context triple: [Jämtland County, borderedBy, Trøndelag County]
  • A. Trøndelag County chosen
    Trøndelag County is a large region in central Norway known for its historic city of Trondheim, coastal and fjord landscapes, and role as a cultural and economic hub of the country.
  • B. Hedmark
    Hedmark is a former county in eastern Norway known for its vast forests, agriculture, and inland landscapes along the Swedish border.
  • C. Sogn og Fjordane
    Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
  • D. Hedmarken
    Hedmarken is a traditional district in Innlandet county in eastern Norway, known for its agricultural landscapes and its central town, Hamar.
  • E. Nordland county
    Nordland county is a long, coastal region in northern Norway known for its dramatic fjords, islands, and Arctic landscapes.
  • 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_69d886d15af4819092f92f8a129763e6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f2d73c3c81908b875023bb925edb completed April 18, 2026, 9:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0c676bbdac8190807ad999c0bd6164 completed May 19, 2026, 1:36 p.m.
Created at: April 10, 2026, 5:36 a.m.