Triple

T17044824
Position Surface form Disambiguated ID Type / Status
Subject Åkrehamn E413537 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Haugesund NE NERFINISHED

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: Haugesund | Statement: [Åkrehamn, hasNearbySettlement, Haugesund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haugesund
Context triple: [Åkrehamn, hasNearbySettlement, Haugesund]
  • A. Haugesund chosen
    Haugesund is a coastal city in southwestern Norway known for its maritime heritage, shipbuilding industry, and annual film and jazz festivals.
  • B. Farsund
    Farsund is a coastal town and municipality in southern Norway known for its maritime heritage, beaches, and historic wooden architecture.
  • C. Nordfjordeid
    Nordfjordeid is a village in western Norway known as a regional center in Nordfjord and the birthplace of mathematician Sophus Lie.
  • D. Austevoll
    Austevoll is a Norwegian island municipality known for its fishing industry and scenic coastal landscape, located off the west coast in the former county of Hordaland.
  • E. Sunndalsøra
    Sunndalsøra is a village and industrial center in western Norway known for its aluminum production and dramatic fjord and mountain surroundings.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d886cd18288190b006abab23f811b7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3da9c112c81908232dc6908d831cf completed April 18, 2026, 7:25 p.m.
Created at: April 10, 2026, 5:33 a.m.