Triple

T15216738
Position Surface form Disambiguated ID Type / Status
Subject Sogn region E363655 entity
Predicate containsSettlement P847 FINISHED
Object Lærdalsøyri E363659 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: Lærdalsøyri | Statement: [Sogn region, containsSettlement, Lærdalsøyri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lærdalsøyri
Context triple: [Sogn region, containsSettlement, Lærdalsøyri]
  • A. Lærdalsøyri chosen
    Lærdalsøyri is a historic village in western Norway known for its well-preserved wooden buildings and location at the inner end of the Sognefjord.
  • B. Byrkjedal
    Byrkjedal is a small rural village in southwestern Norway, known for its scenic valley setting and traditional Norwegian countryside character.
  • C. Hynnekleiv
    Hynnekleiv is a small village in the municipality of Froland in Agder county, southern Norway.
  • D. Reinsvoll
    Reinsvoll is a village in Innlandet county, Norway, known as a local settlement within Vestre Toten municipality.
  • E. Dælenenga
    Dælenenga is an area in Oslo, Norway, known for its sports facilities and urban character within the inner-city district.
  • 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_69fed343f51481908f04c35d37b39ad2 completed May 9, 2026, 6:25 a.m.
Created at: April 10, 2026, 3:11 a.m.