Triple

T15216818
Position Surface form Disambiguated ID Type / Status
Subject Sogn og Fjordane traditional district E363656 entity
Predicate hasWaterBody P165 FINISHED
Object Sunnfjord E1182211 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: Sunnfjord | Statement: [Sogn og Fjordane traditional district, hasWaterBody, Sunnfjord]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sunnfjord
Context triple: [Sogn og Fjordane traditional district, hasWaterBody, Sunnfjord]
  • A. Sunnfjord chosen
    Sunnfjord is a district in Vestland county in Western Norway, known for its fjords, valleys, and traditional rural communities.
  • B. Flekkefjord
    Flekkefjord is a coastal town in southern Norway known for its historic wooden architecture, maritime heritage, and picturesque fjord setting.
  • C. Sifjord
    Sifjord is a small coastal village in northern Norway, situated on the island of Senja within Troms og Finnmark county.
  • D. Freifjord
    Freifjord is a fjord in western Norway known for its scenic coastal landscape and proximity to historic sites such as Kvernes Church.
  • E. Nusfjord
    Nusfjord is a historic fishing village in Norway’s Lofoten archipelago, known for its well-preserved wooden rorbuer cabins and scenic coastal setting.
  • 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_69d85a0ce24c81909c4d3b6475548c95 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0076f90c481909989befe031a2cae completed April 15, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0167369d9481909015c34d475fac14 completed May 11, 2026, 5:20 a.m.
Created at: April 10, 2026, 3:11 a.m.