Triple

T7508205
Position Surface form Disambiguated ID Type / Status
Subject Horten E177445 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Åsgårdstrand E537544 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: Åsgårdstrand | Statement: [Horten, hasNearbySettlement, Åsgårdstrand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Åsgårdstrand
Context triple: [Horten, hasNearbySettlement, Åsgårdstrand]
  • A. Åsgårdstrand chosen
    Åsgårdstrand is a small coastal town in Norway best known as a summer retreat and artistic hub associated with painter Edvard Munch.
  • B. Sogndalstrand
    Sogndalstrand is a historic coastal village in southwestern Norway known for its well-preserved wooden buildings and picturesque harbor setting.
  • C. Nordstrand
    Nordstrand is a mainly residential borough in the southeastern part of Oslo, Norway, known for its hillside location overlooking the Oslofjord.
  • D. Nordstrand
    Nordstrand is a popular sandy beach area on the North Sea island of Norderney in Germany, known for its coastal scenery and recreational opportunities.
  • E. Balestrand
    Balestrand is a picturesque village in western Norway known for its fjordside scenery, historic wooden hotels, and role as a gateway to exploring the Sognefjord region.
  • 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_69c69f276b108190af2cc790b6554544 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f5b8ab5c8190828ee8d144068828 completed March 27, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83ca56e3c81908c3bae8ad2d9ecd1 completed March 28, 2026, 8:40 p.m.
Created at: March 27, 2026, 3:45 p.m.