Triple

T16242841
Position Surface form Disambiguated ID Type / Status
Subject Askøy E394295 entity
Predicate includesVillage P4011 FINISHED
Object Hanevik 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: Hanevik | Statement: [Askøy, includesVillage, Hanevik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanevik
Context triple: [Askøy, includesVillage, Hanevik]
  • A. Hanevik chosen
    Hanevik is a small village in western Norway located within Askøy Municipality in Vestland county.
  • B. Bjerke
    Bjerke is a neighborhood in the Bjerke borough of Oslo, Norway, known primarily as a residential area with local services and amenities.
  • C. Hjelteryggen
    Hjelteryggen is a small settlement located in Fjell municipality in Vestland county on the western coast of Norway.
  • D. Hauge
    Hauge is a small village in Bremanger Municipality in Vestland county, Norway, known for its coastal setting amid rugged fjord and mountain landscapes.
  • E. Kvikne
    Kvikne is a rural village area in central Norway, known historically for mining and as the birthplace of Nobel Prize–winning writer Bjørnstjerne Bjørnson.
  • 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_69d87f2171208190951025e526947816 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e24560060c8190ace4f4c0bd0d886d completed April 17, 2026, 2:36 p.m.
Created at: April 10, 2026, 5:04 a.m.