Triple

T15663453
Position Surface form Disambiguated ID Type / Status
Subject Sogndal E376625 entity
Predicate locatedIn P40 FINISHED
Object Sogn region E363655 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: Sogn region | Statement: [Sogndal, locatedIn, Sogn region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sogn region
Context triple: [Sogndal, locatedIn, Sogn region]
  • A. Sogn region chosen
    The Sogn region is a traditional district in western Norway known for its dramatic fjord landscapes, including the famous Sognefjord, and its rich cultural and historical heritage.
  • B. North Denmark Region
    North Denmark Region is an administrative region in northern Denmark that encompasses the northernmost part of the Jutland Peninsula, including Aalborg as its largest city.
  • C. Ringkjøbing County
    Ringkjøbing County was a former administrative county in western Jutland, Denmark, that existed until the 2007 municipal reform reorganized the country’s regional structure.
  • D. Østlandet
    Østlandet is the most populous region of southeastern Norway, encompassing the capital city Oslo and surrounding inland and coastal areas.
  • E. Viborg County
    Viborg County was a former administrative county in central Jutland, Denmark, that existed until the 2007 municipal reform reorganized it into larger regional units.
  • 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_69d85cd1564c8190991adda63bfab4b0 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f0e2668819092e52712cddd0721 completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff679ff4648190a2f05d6445fa59df completed May 9, 2026, 4:58 p.m.
Created at: April 10, 2026, 4:16 a.m.