Triple

T18327029
Position Surface form Disambiguated ID Type / Status
Subject Vamma power station E439037 entity
Predicate ownedBy P347 FINISHED
Object Glitre Energi NE NERFINISHED

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: Glitre Energi | Statement: [Vamma power station, ownedBy, Glitre Energi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Glitre Energi
Context triple: [Vamma power station, ownedBy, Glitre Energi]
  • A. Glitre Energi Produksjon chosen
    Glitre Energi Produksjon is a Norwegian power generation company focused primarily on producing hydroelectric energy.
  • B. Lyse Energi
    Lyse Energi is a Norwegian energy company that produces and distributes electricity—primarily from hydropower—while also operating related infrastructure and utility services.
  • C. Energetica
    Energetica is an interactive exhibition at Amsterdam’s NEMO Science Museum that explores the principles and applications of sustainable energy and natural forces.
  • D. Energodar
    Energodar is a Ukrainian city best known for hosting the Zaporizhzhia Nuclear Power Plant, the largest nuclear power station in Europe.
  • E. Kenergy
    Kenergy is a playful pop-culture term capturing the exuberant, slightly oblivious yet endearing masculine vibe embodied by Ryan Gosling’s portrayal of Ken in the Barbie movie.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b916a2d081909e249e4902f6aad9 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50aab3e7c81909b1c0a688707dfd6 completed April 19, 2026, 5:02 p.m.
Created at: April 10, 2026, 10:36 a.m.