Triple

T20018270
Position Surface form Disambiguated ID Type / Status
Subject Fræna E494779 entity
Predicate administrativeCentre P1474 FINISHED
Object Elnesvågen 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: Elnesvågen | Statement: [Fræna, administrativeCentre, Elnesvågen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elnesvågen
Context triple: [Fræna, administrativeCentre, Elnesvågen]
  • A. Elnesvågen chosen
    Elnesvågen is a small coastal village in western Norway, situated in the county of Møre og Romsdal.
  • B. Kjerknesvågen
    Kjerknesvågen is a small coastal village in the municipality of Inderøy in Trøndelag county, Norway, known for its scenic fjordside setting and rural character.
  • C. Fosnavåg
    Fosnavåg is a small coastal town in western Norway known for its maritime industries and scenic North Sea surroundings.
  • D. Vossevangen
    Vossevangen is a village in western Norway that serves as the main commercial and cultural hub of the Voss region, known for its scenic surroundings and outdoor activities.
  • E. Brattvåg
    Brattvåg is a small coastal village in western Norway known for its maritime industry and scenic fjord landscape.
  • 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6623e40748190b1abb0ead9acab4e completed April 20, 2026, 5:28 p.m.
Created at: April 11, 2026, 3:34 p.m.