Triple

T15302809
Position Surface form Disambiguated ID Type / Status
Subject Kinsarvik E365828 entity
Predicate near P350 FINISHED
Object Lofthus E379476 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: Lofthus | Statement: [Kinsarvik, near, Lofthus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lofthus
Context triple: [Kinsarvik, near, Lofthus]
  • A. Lofthus chosen
    Lofthus is a village in Norway’s Hardanger region, known for its fruit orchards, fjord scenery, and role as a gateway to hiking routes like the Hardangervidda plateau.
  • B. Gisundet
    Gisundet is a narrow strait in northern Norway that separates the island of Senja from the mainland and connects the Malangen fjord to the Gisundet sound.
  • C. Vennesla
    Vennesla is a municipality in Agder county in southern Norway, known for its industrial heritage and scenic river valley setting.
  • D. Lessebo
    Lessebo is a small locality and municipality in southern Sweden known for its traditional paper mill and glassmaking heritage.
  • E. Mortensrud
    Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
  • 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03ccd575c8190aa43262d3b73ef3c completed April 16, 2026, 1:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a000ebe275c819094473d37cf33c7d0 completed May 10, 2026, 4:51 a.m.
Created at: April 10, 2026, 3:15 a.m.