Triple

T4174820
Position Surface form Disambiguated ID Type / Status
Subject Reisa National Park E86450 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Storslett E394316 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: Storslett | Statement: [Reisa National Park, hasNearbySettlement, Storslett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Storslett
Context triple: [Reisa National Park, hasNearbySettlement, Storslett]
  • A. Storslett chosen
    Storslett is a small village and administrative center in Nordreisa Municipality in Troms og Finnmark county in northern Norway.
  • B. Solbo
    Solbo is a locality within Botkyrka Municipality in Stockholm County, Sweden.
  • C. Blakstad
    Blakstad is a village in Agder county, Norway, known as the main local hub for services and administration in the surrounding Froland area.
  • D. 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.
  • E. Hafslund
    Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
  • 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_69aed93de98c8190ad838ce507b77c8a completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02e9370481908eda048724261c2b completed March 9, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b589f2d7988190b59f0f119f66c046 completed March 14, 2026, 4:16 p.m.
Created at: March 9, 2026, 3:45 p.m.