Triple

T6762302
Position Surface form Disambiguated ID Type / Status
Subject Vegårshei E154623 entity
Predicate hasDemonym P191 FINISHED
Object Vegårsheiing E154623 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: Vegårsheiing | Statement: [Vegårshei, hasDemonym, Vegårsheiing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vegårsheiing
Context triple: [Vegårshei, hasDemonym, Vegårsheiing]
  • A. Vegårshei chosen
    Vegårshei is a rural municipality in Agder county in southern Norway, known for its forests, lakes, and traditional inland communities.
  • B. Engerdal
    Engerdal is a sparsely populated municipality in Innlandet county, Norway, known for its vast forests, lakes, and proximity to the Swedish border.
  • C. Finnvollheia
    Finnvollheia is a mountain that forms the highest point in the Fosen district of Trøndelag, Norway.
  • D. Sørenga
    Sørenga is a modern waterfront neighborhood in Oslo, Norway, known for its residential developments, seaside promenade, and popular public seawater pool and beach.
  • E. Bjugn
    Bjugn is a former municipality and coastal community in Trøndelag county, Norway, known for its fishing, agriculture, and location on the Fosen peninsula.
  • 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_69c688109c1c8190added9a221292af0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d21444dc8190a290af86c81e96a5 completed March 27, 2026, 6:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8a1f8da648190987fad6e37620cef completed March 29, 2026, 3:52 a.m.
Created at: March 27, 2026, 2:12 p.m.