Triple

T13614405
Position Surface form Disambiguated ID Type / Status
Subject Evje og Hornnes E325273 entity
Predicate locatedInRegion P40 FINISHED
Object Setesdal E325272 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: Setesdal | Statement: [Evje og Hornnes, locatedInRegion, Setesdal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Setesdal
Context triple: [Evje og Hornnes, locatedInRegion, Setesdal]
  • A. Setesdal region chosen
    The Setesdal region is a traditional valley area in southern Norway known for its distinctive folk culture, music, and well-preserved rural landscapes.
  • B. Lessebo
    Lessebo is a small locality and municipality in southern Sweden known for its traditional paper mill and glassmaking heritage.
  • C. Namdalseid
    Namdalseid is a former rural municipality in Trøndelag county, Norway, known for its forests, agriculture, and coastal landscape along the Namsenfjorden.
  • D. Svelvik
    Svelvik is a small coastal town and former municipality in Vestfold og Telemark county, Norway, situated along the Drammensfjord.
  • E. Bergvik
    Bergvik is a small locality in central Sweden situated within Söderhamn Municipality in Gävleborg County.
  • 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_69d8076aae28819092cf636190ee5529 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb0abe1208190a1e0a32dc141d836 completed April 12, 2026, 2:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77f9cbc388190972e949324144d2f completed May 3, 2026, 5:02 p.m.
Created at: April 9, 2026, 9:50 p.m.